Task Conflict Research Articles

부하 상사 간 관계 갈등에 대한 업무 갈등과 감성지능의 상호작용 연구

This study investigates the moderating role of emotional intelligence (EI) in the spillover of task conflict into relationship conflict in subordinate-supervisor relationships. Grounded in the ability-based EI model, the research focuses on the emotion management ability of subordinates. Data were collected from 113 employees through an online survey, followed by hierarchical regression analysis. Findings revealed a significant negative relationship between EI and relationship conflict. Additionally, a significant positive link was observed between task conflict and relationship conflict. Emotional intelligence significantly moderates this relationship, with higher EI attenuating the spillover effect of task conflict on relationship conflict. In summary, employees with higher EI effectively manage interpersonal conflicts with their supervisors, fostering constructive interactions. Furthermore, subordinates’ EI acts as a buffering moderator, preventing task conflict from transforming into relationship conflict. This research offers practical implications and suggests avenues for future inquiry.

The time course of the spatial representation of ‘past’ and ‘future’ concepts: New evidence from the STEARC effect

Humans use space to think of and communicate the flow of time. This spatial representation of time is influenced by cultural habits so that in left-to-right reading cultures, short durations and past events are mentally positioned to the left of long durations and future events. The STEARC effect (Space Temporal Association of Response Codes) shows a faster classification of short durations/past events with responses on the left side of space and of long durations/future events with responses on the right side. We have recently showed that during the classification of time durations, space is a late heuristic of time because in this case, the STEARC appears only when manual responses are slow, not when they are fast. Here, we wished to extend this observation to the semantic classification of words as referring to the ‘past’ or the ‘future’. We hypothesised that the semantic processing of ‘past’ and ‘future’ concepts would have engaged slower decision processes than the classification of short versus long time durations. According to dual-route models of conflict tasks, if the task-dependent classification/decision process were to proceed relatively slowly, then the effects of direct activation of culturally preferred links between stimulus and response (S-R), i.e., past/left and future/right in the case of the present task, should attain higher amplitudes before the instruction-dependent correct response is selected. This would imply that, at variance with the faster classification of time durations, during the slower semantic classification of time concepts, in incongruent trials, the direct activation of culturally preferred S-R links should introduce significant reaction time (RT) costs and a corresponding STEARC at the fastest manual responses in the experiment too. The study's results confirmed this hypothesis and showed that in the classification of temporal words, the STEARC also increased as a function of the length of RTs. Taken together, the results from sensory duration and semantic classification STEARC tasks show that the occurrence, strength and time course of the STEARC varies significantly as a function of the speed and level of cognitive processing required in the task.

A sleepless night disrupts the resolution of emotional conflicts: Behavioural and neural evidence.

The present study aims to investigate the influence of 24-hr sleep deprivation on implicit emotion regulation using the emotional conflict task. Twenty-five healthy young adults completed a repeated-measures study protocol involving a night of at-home normal sleep control and a night of in-laboratory sleep deprivation. Prior to the experimental session, all participants wore an actigraph watch and completed the sleep diary. Following each condition, participants performed an emotional conflict task with electroencephalographic recordings. Emotional faces (fearful or happy) overlaid with words ("fear" or "happy") were used as stimuli creating congruent or incongruent trials, and participants were instructed to indicate whether the facial expression was happy or fearful. We measured the accuracy and reaction time on the emotional conflict task, as well as the mean amplitude of the P300 component of the event-related potential at CPz. At the behavioural level, sleep-deprived participants showed reduced alertness with overall longer reaction times and higher error rates. In addition, participants in the sleep deprivation condition made more errors when the current trial followed congruent trials compared with when it followed incongruent trials. At the neural level, P300 amplitude evoked under the sleep-deprived condition was significantly more positive compared with the normal sleep condition, and this effect interacted with previous-trial and current-trial congruency conditions, suggesting that participants used more attentional resources to resolve emotional conflicts when sleep deprived. Our study provided pioneering data demonstrating that sleep deprivation may impair the regulation of emotional processing in the absence of explicit instruction among emerging adults.

Cognitive Signatures of Depressive and Anhedonic Symptoms and Affective States Using Computational Modeling and Neurocognitive Testing

BackgroundDeeper phenotyping may improve our understanding of depression. Because depression is heterogeneous, extracting cognitive signatures associated with severity of depressive symptoms, anhedonia, and affective states is a promising approach. MethodsSequential sampling models decomposed behavior from an adaptive approach-avoidance conflict task into computational parameters quantifying latent cognitive signatures. Fifty unselected participants completed clinical scales and the approach-avoidance conflict task by either approaching or avoiding trials offering monetary rewards and electric shocks. ResultsDecision dynamics were best captured by a sequential sampling model with linear collapsing boundaries varying by net offer values, and with drift rates varying by trial-specific reward and aversion, reflecting net evidence accumulation toward approach or avoidance. Unlike conventional behavioral measures, these computational parameters revealed distinct associations with self-reported symptoms. Specifically, passive avoidance tendencies, indexed by starting point biases, were associated with greater severity of depressive symptoms (R = 0.34, p = .019) and anhedonia (R = 0.49, p = .001). Depressive symptoms were also associated with slower encoding and response execution, indexed by nondecision time (R = 0.37, p = .011). Higher reward sensitivity for offers with negative net values, indexed by drift rates, was linked to more sadness (R = 0.29, p = .042) and lower positive affect (R = −0.33, p = .022). Conversely, higher aversion sensitivity was associated with more tension (R = 0.33, p = .025). Finally, less cautious response patterns, indexed by boundary separation, were linked to more negative affect (R = −0.40, p = .005). ConclusionsWe demonstrated the utility of multidimensional computational phenotyping, which could be applied to clinical samples to improve characterization and treatment selection.

Modality matters: Three auditory conflict tasks to measure individual differences in attention control.

Early work on selective attention used auditory-based tasks, such as dichotic listening, to shed light on capacity limitations and individual differences in these limitations. Today, there is great interest in individual differences in attentional abilities, but the field has shifted towards visual-modality tasks. Furthermore, most conflict-based tests of attention control lack reliability due to low signal-to-noise ratios and the use of difference scores. Critically, it is unclear to what extent attention control generalizes across sensory modalities, and without reliable auditory-based tests, an answer to this question will remain elusive. To this end, we developed three auditory-based tests of attention control that use an adaptive response deadline (DL) to account for speed-accuracy trade-offs: Auditory Simon DL, Auditory Flanker DL, and Auditory Stroop DL. In a large sample (N = 316), we investigated the psychometric properties of the three auditory conflict tasks, tested whether attention control is better modeled as a unitary factor or modality-specific factors, and estimated the extent to which unique variance in modality-specific factors contributed incrementally to the prediction of dichotic listening and multitasking performance. Our analyses indicated that the auditory conflict tasks have strong psychometric properties and demonstrate convergent validity with visual tests of attention control. Auditory and visual attention control factors were highly correlated (r = .81)-even after controlling for perceptual processing speed (r = .75). Modality-specific attention control factors accounted for unique variance in modality-matched criterion measures, but the majority of the explained variance was modality-general. The results suggest an interplay between modality-general attention control and modality-specific processing.

대학생 TBL·PBL 학습 과정에서 팀 내 과업 갈등이 집단효능감에 미치는 영향 연구

Objectives This study utilized a multilevel approach to investigate the influence of task and relationship conflicts among college team members on collective efficacy during university TBL and PBL classes.
 Methods Over a span of 10 weeks, a total of 176 students were organized into 25 teams participating in a uni-versity calculus mathematics course, which was conducted using TBL and PBL methodologies. At the conclusion of the course, a survey was administered. The study employed a cross-level interaction analysis with random slope models.
 Results The study revealed a significant cross-level moderation effect in the relationship between individual-level task conflict and collective efficacy moderated by team-level relationship conflict. In teams characterized by high relationship conflict, there was a positive correlation between team members' task conflict and collective efficacy. Conversely, in teams with low relationship conflict, team members' task conflict had little impact on collective efficacy. Relationship conflict negatively and significantly affected collective efficacy at both individual and team levels.
 Conclusions This study empirically demonstrated that the influence of team members' task conflict on collective efficacy varies depending on the level of team relationship conflict. This underscores the importance of effective communication during periods of relationship conflict in teams. The study discusses implications for TBL and PBL for both scholars and practitioners.

The contribution of difficulty of an irrelevant task to task conflict.

In the standard colour-word Stroop task, participants are presented with colour words and required to respond to their colour while ignoring their meaning. Two types of conflict might occur in such experiments: information conflict and task conflict. Information conflict reflects the processing of two contradicting pieces of information and is indicated by shorter reaction times (RTs) in congruent than in incongruent trials. Task conflict reflects the additional effort associated with performing two tasks, as opposed to one, and is indicated by shorter RTs in neutral trials than in congruent trials (termed reverse facilitation). While information conflict is commonly seen in Stroop and Stroop-like tasks, task conflict is rarely observed. In the present study, participants were presented with coloured segments that, by applying Gestalt principles, could be perceived as colour words. We found that incongruent trials were slower than congruent trials, suggesting that participants successfully perceived the colour words, which led to involuntary reading. In addition, reversed facilitation was found so that neutral trials (i.e., trials that only consist of one task) were faster than congruent trials (as well as incongruent trials; both consist of two tasks). The presence of both interference from the incongruent trials and reverse facilitation suggests that involuntary reading could also occur in scenarios requiring cognitive effort.

Cognitive Control among Primary- and Middle-School Students and Their Associations with Math Achievement

Background: Math achievement is an important predictor of academic success. While many studies have examined math achievement in young children, studies with older children are scarce. This study focused on primary- and middle-school students, examining math achievements and cognitive control. Cognitive control was assessed referring to both domain-specific and domain-general cognitive control mechanisms and eliciting both simple and complex levels of conflict, and their association with math achievements. Methods: One-hundred-and-twenty-two participants performed two versions of a cognitive control task: a numerical Stroop task (NST; manipulating the numerical and physical size of Arabic numerals) and a perceptual Stroop task (PST; manipulating the location and direction of an arrow). For math achievements, participants performed math fluency and math curriculum tests. Results: Overall, the congruency effect was smaller in older students than in younger ones. Moreover, all participants demonstrated a similar congruency effect in the simple conflict task, whereas younger students showed a larger congruency effect in the complex conflict task. In addition, performance on the basic math fluency task was predicted by both Stroop tasks. However, performance on the comprehensive math achievement test was predicted only by the PST. Conclusions: Our results demonstrated enhanced cognitive control abilities of middle-school students and suggest that they can contribute to math achievements. We call for considering the implementation of both domain-specific and domain-general cognitive control activities as a potential approach to support math achievements.

Stimulus-triggered task conflict affects task-selection errors in task switching: A Bayesian multinomial processing tree modeling approach.

In the present study, we used a modeling approach for measuring task conflict in task switching, assessing the probability of selecting the correct task via multinomial processing tree (MPT) modeling. With this method, task conflict and response conflict can be independently assessed as the probability of selecting the correct task and the probability of selecting the correct response within a given task, respectively. These probabilities can be estimated on the basis of response accuracy in the different experimental conditions. In two task-switching experiments, we used bivalent stimuli and manipulated irrelevant-task difficulty by varying the saliency of the stimulus feature belonging to the irrelevant task. The more salient the task-irrelevant stimulus feature, the more salient the irrelevant task, leading to more task conflict. Consistent with this assumption, we observed that task conflict, but not response conflict, was larger when the task-irrelevant stimulus feature was made more salient. Furthermore, both task conflict and response conflict were larger when the task switched than when the task was repeated. On a methodological level, the present results demonstrate that MPT modeling is a useful approach for measuring task conflict in task switching and for dissociating it from within-task response conflict. Furthermore, the present results inform theories of task switching by showing that the task-irrelevant feature tends to activate the irrelevant task set rather than being associated with a specific response option via a direct stimulus-response route. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Efficient Task-Network Scheduling With Task Conflict Metric in Time-Sensitive Networking

With the rapid development of Industrial Internet of Things (IIoT), Time-Sensitive Networking (TSN) with deterministic and real-time features has gained broad interest. However, most existing research focuses on the network scheduling with fixed task placement and computing resource allocation, restricting the scheduling space of coupled task-network. To tackle this coupling problem, an efficient task-network scheduling (ETNS) scheme is proposed in this paper for time-sensitive networking. A task-conflict metric (TCM) is established to quantify the competition degree of scheduling resources. For increasing the overall scheduling space, a TCM-aware pre-scheduling method is proposed by optimizing task placement and routing paths to reduce the potential conflicts between tasks. Integrated with the pre-scheduling method, we design a TCM-aware parallel group-scheduling algorithm by reducing the conflicts between task groups to enhance schedulability and scalability. Experiments show that our ETNS scheme significantly improves the schedulability and scalability performances compared with the existing scheduling approaches. The larger number of tasks, the higher the performance improvement.

Big data innovation and implementation in projects teams: towards a SEM approach to conflict prevention

PurposeDespite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.Design/methodology/approachThis study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.FindingsResults from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.Research limitations/implicationsThe study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.Practical implicationsThe study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.Social implicationsThe study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.Originality/valueThe study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

Sleep deprivation affects interference control: A diffusion model analysis.

Previous studies suggest that interference control may be unaffected by sleep deprivation based on the unchanged interference effects (reaction time [RT] differences between incongruent and congruent conditions), while ignoring the overall slower RTs after sleep deprivation. In the present study, we interpreted these results from a new angle using a variant of diffusion model, diffusion model for conflict tasks (DMC), and investigated whether and how interference control is affected by sleep deprivation. Mathematical derivations and model simulations showed that unchanged task-irrelevant information processing (i.e., unaffected interference control) may not lead to the observed unchanged interference effects when considering the overall slower RTs after sleep deprivation (due to either decreased drift rate of task-relevant information or increased decision boundary). Therefore, the unchanged interference effects do not necessarily indicate unchanged interference control. We then conducted a Simon task following one night of sleep deprivation or normal sleep, and fitted the DMC to the data. Experimental results showed that the Simon effect was reversed when most of the trials were incongruent, indicating that participants used learned spatially incompatible stimulus-response associations to predict responses. However, the Simon effects in both mean RTs and RT distributions were not significantly modulated by sleep deprivation. Model fits showed that the drift rate of task-relevant information decreased and the time-to-peak of task-irrelevant activation increased after sleep deprivation. These results suggest that central information processing was degraded after sleep loss, and most importantly, task-irrelevant activation increased after sleep deprivation as interference control was impaired. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Conflict detection and resolution in macaque frontal eye fields

Stimulus-induced conflicts in decision-making tasks produce both behavioral and neuronal congruency effects. However, how and when conflicts are detected and resolved at the neuronal level remains largely unclear. To address these issues, we recorded from single neurons in the frontal eye fields of two macaques performing a conflict task. Although the temporal dynamics of the neuronal congruency effects are independent of the specific task rules, they are substantially different in target- and distractor-encoding neurons. Conflicts were detected ~100 ms after the conflict-inducing cue (20–30 ms after the visual response), which is much faster than predicted based on human EEG results. This suggests that conflict detection relies on a fast mechanism in frontal eye fields. Resolving the conflict at the neuronal level, however, requires between <400 ms to ~1000 ms, and shows profound interindividual differences and depends on task rules, indicating that it is a more complex and top-down driven process. Our findings illuminate the neuronal mechanisms underlying decision-making when a conflict is present, a crucial cognitive process playing a role in basic survival and high-level cognitive functions.

Effects of contextualized emotional conflict control on domain-general conflict control: fMRI evidence of neural network reconfiguration.

Domain-general conflict control refers to the cognitive process in which individuals suppress task-irrelevant information and extract task-relevant information. It supports both effective implementation of cognitive conflict control and emotional conflict control. The present study employed functional magnetic resonance imaging and adopted an emotional valence conflict task and the arrow version of the flanker task to induce contextualized emotional conflicts and cognitive conflicts, respectively. The results from the conjunction analysis showed that the multitasking-related activity in the pre-supplementary motor area, bilateral dorsal premotor cortices, the left posterior intraparietal sulcus (IPS), the left anterior IPS and the right inferior occipital gyrus represents common subprocesses for emotional and cognitive conflict control, either in parallel or in close succession. These brain regions were used as nodes in the domain-general conflict control network. The results from the analyses on the brain network connectivity patterns revealed that emotional conflict control reconfigures the domain-general conflict control network in a connective way as evidenced by different communication and stronger connectivity among the domain-general conflict control network. Together, these findings offer the first empirical-based elaboration on the brain network underpinning emotional conflict control and how it reconfigures the domain-general conflict control network in interactive ways.

The Role of Task, Relationship, and Process Conflicts in Shaping Employee Performance in Nepal’s Commercial Bankst

This study aims to assess the impact of workplace disputes—specifically those related to tasks, relationships, and procedures—on the performance of workers at commercial banks in Nepal. The banking sector, characterized by hierarchical structures and intense environments, is particularly susceptible to various forms of conflict. A standardized questionnaire was administered to 200 respondents across different departments of commercial banks, employing a quantitative approach. Correlation and regression analyses were conducted using SPSS to investigate the relationship between workplace disagreements and employee performance. Results indicate that all three types of workplace conflicts—task, interpersonal, and process conflicts—significantly adversely affect employee performance. A moderately negative correlation was found between task conflict and performance (r = -0.45), suggesting that unresolved disagreements can hinder productivity despite potentially fostering discussion. Interpersonal conflict showed a considerable negative impact on performance (B = -0.65), indicating that strained relationships undermine team cohesion and morale. Process conflict significantly affected workflow efficiency (F = 6.82, p = 0.005). The study also revealed that employee experience moderates the relationship between task conflict and performance, with more experienced employees managing conflicts more effectively. These findings underscore the need for tailored conflict resolution strategies to mitigate the negative effects of workplace disputes. Keywords: workplace conflict, employee performance, task conflict, relationship conflict, conflict management

How to Foster Project Citizenship Behavior in Construction Industry: Organizational Culture Matters

Seller's project citizenship behavior has recently received much attention due to its role in promoting project success and improving the performance of both the overall project and of each stakeholder. However, previous studies have paid insufficient attention to how organizational culture affects a seller's project citizenship behavior, especially in the context of interorganizational conflicts. Therefore, this study explores the influence mechanism of three dimensions of seller's organizational culture with spillover effects (social responsibility, customer orientation, and innovation) on employees’ project citizenship behavior, and investigates the moderating role of interorganizational conflict (task conflict, relationship conflict, and conflict profiles) in the relationship between organizational culture and project citizenship behavior. Based on 248 surveys gathered from the Chinese construction industry, the empirical results show that the social responsibility and customer orientation of a seller's organizational culture have a significant positive impact on the project citizenship behavior of its employees. Meanwhile, interorganizational task conflict negatively moderates the relationship between customer orientation and project citizenship behavior, while relationship conflict positively moderates it. Moreover, the conflict state profile with low task conflict and high relationship conflict is most conducive to enhancing the positive impact of customer orientation on project citizenship behavior. This article reveals the impact of the spillover effect of a seller's organizational culture on its employees’ project citizenship behavior, contributes to organizational culture theory in terms of its spillover effect and the impact on promoting the development of project citizenship behavior, and provides practical guidance for construction practitioners.

Common and distinct BOLD correlates of Simon and flanker conflicts which can(not) be reduced to time-on-task effects.

The ability to identify and resolve conflicts between standard, well-trained behaviors and behaviors required by the current context is an essential feature of cognitive control. To date, no consensus has been reached on the brain mechanisms involved in exerting such control: while some studies identified diverse patterns of activity across different conflicts, other studies reported common resources across conflict tasks or even across simple tasks devoid of the conflict component. The latter reports attributed the entire activity observed in the presence of conflict to longer time spent on the task (i.e., to the so-called time-on-task effects). Here, we used an extended Multi-Source Interference Task (MSIT) which combines Simon and flanker types of interference to determine shared and conflict-specific mechanisms of conflict resolution in fMRI and their separability from the time-on-task effects. Large portions of the activity in the dorsal attention network and decreases of activity in the default mode network were shared across the tasks and scaled in parallel with increasing reaction times. Importantly, the activity in the sensory and sensorimotor cortices, as well as in the posterior medial frontal cortex (pMFC) - a key region implicated in conflict processing - could not be exhaustively explained by the time-on-task effects.

Error-related negativity: dynamics of a neurocognitive sensitivity marker to decision mismatch in psychiatric disorders. Part 2

The transformation of methodological ideas about ERN as a significant neurocognitive marker for clarifying the mechanisms of development and maintenance of mental disorders are analyzed. The potential is registered in the anterior cingulate cortex 50–100 ms after making an error in the conflict task and acts as a neurocognitive indicator of sensitivity to decision mismatches. Comprehension of the provisions on the error monitoring system is discussed depending on the peculiarities of the clinical group definition, different conditions of activity (error of another or one’s own, motivational significance, attitude to accuracy, uncertainty, awareness of the error and other), as well as individual-typological characteristics. The significance of the error monitoring system in the context of the transition from a categorical to a dimensional approach to the classification of mental disorders is conceptualized, and inconsistencies in the data are discussed. ERN is considered as a modulation pattern of the internalisation-externalisation spectrum of psychopathology, acting as a dimensional psychopathological model that partially overcomes the problems of comorbidity. Based on the idea of defining ERN as a transdiagnostic electrophysiological marker of mental health, highly comorbid disorders, the problem of comparing the features of the error monitoring system in anxiety and psychotic disorders is analyzed. Studies show specific strengthening of the ERN in anxiety disorders and weakening in psychosis, but some components of the ERN in psychotic disorders may remain preserved, and under certain conditions of activity, error detection is intact. The qualitative rearrangements in the error monitoring system in psychosis reveal a more complex psychological structure of error identification than the observation of a decline in this ability.

An Asymmetric Feature Enhancement Network for Multiple Object Tracking of Unmanned Aerial Vehicle

Multiple object tracking (MOT) in videos captured by unmanned aerial vehicle (UAV) is a fundamental aspect of computer vision. Recently, the one-shot tracking paradigm integrates the detection and re-identification (ReID) tasks, striking a balance between tracking accuracy and inference speed. This paradigm alleviates task conflicts and achieves remarkable results through various feature decoupling methods. However, in challenging scenarios like drone movements, lighting changes and object occlusion, it still encounters issues with detection failures and identity switches. In addition, traditional feature decoupling methods directly employ channel-based attention to decompose the detection and ReID branches, without a meticulous consideration of the specific requirements of each branch. To address the above problems, we introduce an asymmetric feature enhancement network with a global coordinate-aware enhancement (GCAE) module and an embedding feature aggregation (EFA) module, aiming to optimize the two branches independently. On the one hand, we develop the GCAE module for the detection branch, which effectively merges rich semantic information within the feature space to improve detection accuracy. On the other hand, we introduce the EFA module for the ReID branch, which highlights the significance of pixel-level features and acquires discriminative identity embedding through a local feature aggregation strategy. By efficiently incorporating the GCAE and EFA modules into the one-shot tracking pipeline, we present a novel MOT framework, named AsyUAV. Extensive experiments have demonstrated the effectiveness of our proposed AsyUAV. In particular, it achieves a MOTA of 38.3% and IDF1 of 51.7% on VisDrone2019, and a MOTA of 48.0% and IDF1 of 67.5% on UAVDT, outperforming existing state-of-the-art trackers.

A small object detection algorithm based on feature interaction and guided learning

At present, for the diverse target sizes, different angles, and complex environment in aerial images, how to detect small objects effectively in aerial images is still a challenge task. In order to further improve the detection accuracy and reduce the missing rate, in this paper, we proposes a small target detection algorithm based on feature interaction and guided learning. Firstly, the feature guided alignment module is designed to deal with the problem of information loss and overlap. Secondly, the misallocation of small object samples is optimized by introducing gaussian sample allocation strategy. Then the interactive parallel detection header is designed to solve the detection task conflict problem. Finally, the new regression loss function is designed to enhance the localization ability of the target. The experimental results on the Tinyperson dataset and Visdrone dataset show that this model can improve the detection accuracy and reduce the missing rate of small targets effectively.