Images Of Animals Research Articles

Ensemble representation of animacy could be based on mid-level visual features.

Studies suggest that mid-level features could underlie object animacy perception. In the current research, we tested whether ensemble animacy perception is based on high- or mid-level features. We used five types of images of animals and inanimate objects: color, grayscale, silhouettes, texforms - unrecognizable images that preserve mid-level texture and shape information - and scrambled images. In the series of Experiments 1, we asked participants to evaluate the animacy of single images and sets of eight images using a 10-point scale. In the series of Experiments 2, participants were shown two sets of eight images and had to choose a more animate one in the two-alternative forced-choice (2AFC) task. We found that in both paradigms, observers could report the mean animacy of the set of texform images without direct access to information about high-level features. Thus, ensemble animacy could be extracted only based on mid-level features such as shape and texture without access to more high-level information.

Feature Weighted Cycle Generative Adversarial Network with Facial Landmark Recognition and Perceptual Color Distance for Enhanced Face Animation Generation

We propose an anime style transfer model to generate anime faces from human face images. We improve the model by modifying the normalization function to obtain more feature information. To make the face feature position of the anime face similar to the human face, we propose facial landmark loss to calculate the error between the generated image and the real human face image. To avoid obvious color deviation in the generated images, we introduced perceptual color loss into the loss function. In addition, due to the lack of reasonable metrics to evaluate the quality of the animated images, we propose the use of Fréchet anime inception distance to calculate the distance between the distribution of the generated animated images and the real animated images in high-dimensional space, so as to understand the quality of the generated animated images. In the user survey, up to 74.46% of users think that the image produced by the proposed method is the best compared with other models. Also, the proposed method reaches a score of 126.05 for Fréchet anime inception distance. Our model performs the best in both user studies and FAID, showing that we have achieved better performance in human visual perception and model distribution. According to the experimental results and user feedback, our proposed method can generate results with better quality compared to existing methods.

Gait Analysis through Animated GIFs: A Novel Approach for Visualizing Step Dynamics

The field of prosthetic knee development has made great progress in recent years, notably with the use of machine learning (ML) approaches. Researchers made significant progress in enhancing the functionality, flexibility, and user experience of prosthetic knees using revolutionary machine learning techniques.Since gait analysis delivers part of the most important information about human motion patterns, it becomes critical in the development of a prosthetic knee. In this paper, some new techniques for gait analysis with feature extraction are proposed that include visualization using animated GIF images. This methodology extracts key parameters like step length and step width from the frames of a GIF image and can completely represent the dynamics of gait with respect to time.This methodology is particularly significant to design an efficient prosthetic knee since it shows how combining computer analysis and visual data may enhance gait analysis methods. For this study, brief walking footage of both healthy individuals and amputees are recorded, then turned into GIFs. Subsequently, these GIF data points are retrieved, making it possible to quantify step length and other essential metrics required to analyses gait patterns.Gait analysis is incorporated as part of the development process for these prosthetic knee joints due to the fact that it gives information on human motion patterns. The methods used in this paper provide novel ways of carrying out gait analysis through feature extraction and visualization using animated GIF images. This method would help in depicting the full picture of gait dynamics with time and assist in extracting important parameters such as step length and width from the frames of the GIF. The work, as described, falls squarely into the use of computer vision techniques for feature extraction and into time-series data analysis for trend identification within the broader application of machine learning in the development of the prosthetic knee. These techniques could be generalized toward designing better prosthetic knee design for more natural and fluent motion.

Digital animal deathscapes: The online circulation of animals killed for conservation

AbstractThis paper brings together animals, death, and digital geographies to examine the sharing of dead animal imagery on social media by conservationists in Aotearoa New Zealand (NZ). It is particularly concerned with two key questions: (1) Why (and how) do dead animals attract support for conservation? (2) How are personal feelings about animal death navigated in the public space of social media? In answering these questions, this paper extends geographical research on animals' affective allures (including online) beyond the realm of the living, and contributes to ongoing conversations around how to live with ‘unwanted others’. I draw on interviews with the leaders of conservation groups about whether, when, and why they post images of dead animals and kill counts, which I collectively refer to as ‘death media’. I show that because some viewers (at times disparaged as ‘precious’) were expected to respond with physical and/or moral disgust, conservationists typically only share death on ‘mainstream’ platforms if it is sufficiently sanitised or incorporated into positive narratives—though more commonly, death is absent from these platforms. Other audiences, particularly volunteer trappers, were described as ‘pragmatic’ or ‘bloodthirsty’; death was shared with these audiences to cultivate affects of hope and solidarity, in a context where killing can affectively feel like success. Yet even those comfortable with both killing and viewing death media at times expressed regret and sadness at the deaths of pests; they simply avoid sharing these feelings online. Death media thus perpetuate the public un‐grievability of ‘pests’, despite indications that even those who do the work of killing may experience sadness privately. I conclude by asking: what would be needed for pests killed for conservation to become grievable online, and how could doing so change relationships between humans and ‘pest’ animals?

Reflected encounters at hunter-gatherer rock art sites by the water

ABSTRACT This article seeks to recapture the sensory experiences of prehistoric hunter-gatherers in the Finnish Lake District by examining the acoustics of their rock art sites. The sites consist of vertical cliffs rising directly from the lakes, with painted images of humans, boats, and animals, sometimes also drummers (5000–1500 calBC). The acoustic impulse response measurements performed at 37 sites indicate that the painted cliffs, in their original state, reflected sound more strongly and accurately than the nearby lakeshore rocks. The psychoacoustic criterion and the auralizations created through artistic improvisations indicate that the reflections generated discrete single-repeat echoes, which endowed sounds produced in front of the cliffs with their auditory mirror images. As these reflections appeared to emanate from invisible sources behind the paintings, the auditory and visual images overlapped merging into one multisensory experience. Although the sounds and music of prehistoric people are beyond our reach, the study shows that the physical environment actively participated in their activities, co-vibrating and creating reciprocal tangible encounters between the human and more-than-human worlds. For the history of sound and music, the study provides an example of how significant a role sound reflections could have in past societies.

Research and Application of Chinese Auspicious Animal Images in Contemporary Clothing Design—Take “The Classic of Mountains and Seas” as Research Example

This thesis aims to investigate the auspicious animal images in “The Classic of Mountains and Seas”, exploring the profiling features and evolution of the auspicious animal patterns through cross verification of images, literature and cultural relics, and based on the research, the images are applied on the China-Chic clothing design. Ancient Chinese took the auspicious animals as things of blessing, which were endowed with many beautiful meanings to express our ancestors’ longing for a better life. Based on the concept of innovative design derived from the traditional culture, this thesis takes the images of auspicious animals in “The Classic of Mountains and Seas” as its research object to analyze their origins and evolution in China-chic fashion and, together with the case study of modern clothing design and a certain extent summary, to promote the inheritance, development and application of traditional culture in modern social life. The thesis will delve deep into the cultural connotations and aesthetic characteristics of the auspicious animal images, analyze and investigate the types, characteristics and implied meanings of such image to extract representative visual element symbols, which are then integrated into the modern fashion design, fulfilling the inheritance, development and application of traditional culture in modern social life.

Film image processing and production based on high-performance calculation

In film and television production, efficient and precise image processing is vital for achieving realistic visual effects. Therefore, exploring and applying advanced image processing technologies has become an essential method for elevating the production quality of film and television projects. This work investigates the application of artificial intelligence (AI) technology in the processing and production of animated images in film and television scenarios. By comparing the performance of standard Generative Adversarial Network (GAN), DenseNet, and CycleGAN models under different noise conditions, it is found that CycleGAN performs the best in image denoising and detail restoration. Experimental results demonstrate that CycleGAN achieves a Peak Signal-to-noise Ratio (PSNR) of 30.1dB and a Structural Similarity Index Measure (SSIM) of 0.88 under Gaussian noise conditions. Moreover, CycleGAN achieves a PSNR of 29.5dB and an SSIM of 0.85 under salt-and-pepper noise conditions. It outperforms the other models in both conditions. Additionally, CycleGAN’s mean absolute error is significantly lower than that of the other models. This work demonstrates that CycleGAN can more effectively handle complex noise and generate high-quality images under unsupervised learning conditions. These findings provide new directions for future image processing research and offer important references for model selection in practical applications. This work not only offers new perspectives on the development of animation image processing technology but also establishes a theoretical foundation for applying advanced AI techniques in film and television production. Through comparative analysis of various deep learning models, this work highlights the superior performance of CycleGAN under complex noise conditions. This advancement not only drives progress in image processing technology but also provides effective solutions for efficient production and quality enhancement of future film and television works.

“Cute saves the world!”: animal Internet Celebrities’ cute activism in the #adoptdon’tshop animal rescue campaign on social media

ABSTRACT This paper examines everyday media practices and seamless work in animal advocacy by various actors with different levels of internet celebrity status, who curate their media personas around ‘cute’ animal images, including established pet Influencers and animal internet celebrities. Through a case study of the most prominent (hashtag) campaign and movement against the pet trade industry and culture in South Korea, #AdoptDon’tShop [#사지말고입양하세요, sajimalgo-ipyanghaseyo], I explore animal internet celebrities’ media practices and immaterial labor that are understated but rigorously performed out of compassion and care for animals. Taking up scholarship on cuteness and Influencer culture, I introduce the concept of cute activism, a novel iteration of social movements adapted into visual social media cultures, pivoting on the performative potential of cuteness and its inherent competency in navigating increasingly-visualized, attention-seeking social media environments. While the instinctive affective appeal of cuteness serves as a driving force and primary modality of cute activism, effectively attracting more people to be tuned into messages, events, and ultimately movements, the very appeal may come into being as a burden for activists, inducing them into continuous immaterial labor.

Impact of Pre-trained Weights on MobileNet Architectures for Animal Classification

This study aims to address the problem of improving animal image classification accuracy using different versions of MobileNet. Accurate animal classification plays a vital role in biodiversity protection, environmental monitoring, and agriculture. The research is significant because existing studies focus on specific models and datasets, leaving a gap in the comparative performance analysis of MobileNet versions. To address this issue, MobileNet V1, V2, and V3 models were utilized, both with and without ImageNet pre-trained weights. The models were trained on a dataset composed of 30,179 images from two sources, covering 13 animal categories. The experiment involved training the models over 10 epochs using a standard configuration of the TensorFlow framework, with accuracy serving as the primary evaluation metric.The results showed that MobileNet V3Large, with pre-trained weights, achieved the highest accuracy (97.43%), outperforming V1 and V2. Using pre-trained weights consistently enhanced performance, as models without pre-training exhibited lower accuracy and slower convergence. This study contributes by providing a comprehensive comparison of MobileNet versions in animal classification tasks, demonstrating the importance of pre-training and model architecture optimization for achieving high accuracy in image classification.

Controllable Anime Image Editing via Probability of Attribute Tags

AbstractEditing anime images via probabilities of attribute tags allows controlling the degree of the manipulation in an intuitive and convenient manner. Existing methods fall short in the progressive modification and preservation of unintended regions in the input image. We propose a controllable anime image editing framework based on adjusting the tag probabilities, in which a probability encoding network (PEN) is developed to encode the probabilities into features that capture continuous characteristic of the probabilities. Thus, the encoded features are able to direct the generative process of a pre‐trained diffusion model and facilitate the linear manipulation. We also introduce a local editing module that automatically identifies the intended regions and constrains the edits to be applied to those regions only, which preserves the others unchanged. Comprehensive comparisons with existing methods indicate the effectiveness of our framework in both one‐shot and linear editing modes. Results in additional applications further demonstrate the generalization ability of our approach.

EthoWatcher OS: improving the reproducibility and quality of categorical and morphologic/kinematic data from behavioral recordings in laboratory animals.

Behavioral recordings annotated by human observers (HOs) from video recordings are a fundamental component of preclinical animal behavioral models of neurobiological diseases. These models are often criticized for their vulnerability to reproducibility issues. Here, we present the EthoWatcher-Open Source (EW-OS), with tools and procedures for the use of blind-to-condition categorical transcriptions that are simultaneous with tracking, for the assessment of HOs intra- and interobserver reliability during training and data collection, for producing video clips of samples of behavioral categories that are useful for observer training. The use of these tools can inform and optimize the performance of observers, thus favoring the reproducibility of the data obtained. Categorical and machine vision-derived outputs are presented in an open data format for increased interoperability with other applications, where behavioral categories are associated frame-by-frame with tracking, morphological and kinematic attributes of an animal's image. The center of mass (X and Y pixel coordinates), the animal's area in square millimeters, the length and width in millimeters, and the angle in degrees were recorded. It also assesses the variation in each morphological descriptor to produce kinematic descriptors. While the initial measurements are in pixels, they are later converted to millimeters using the scale calibrated by the user via the graphical user interfaces. This process enables the creation of databases suitable for machine learning processing and behavioral pharmacology studies. EW-OS is constructed for continued collaborative development, available through an open-source platform, to support initiatives toward the adoption of good scientific practices in behavioral analysis, including tools for evaluating the quality of the data that can alleviate problems associated with low reproducibility in the behavioral sciences.

More than tough luck

Abstract Applied Cognitive Linguistics (ACL, henceforth) offers a vision of language closely tied to our experiences and views of the world, showing great promise for foreign language teaching and learning. Building upon this meaning-centered perspective, this paper discusses an interventional, quasi-experimental study assessing the effectiveness of incorporating animated images into materials for teaching comparative constructions in L2 Spanish. Conducted in three phases with varying participation rates (69 students in the first, 18 in the second, and 27 in the third), the study faced numerous factors that hindered data collection process and thereby influenced the results. Although the findings were not statistically significant, they suggest a slight improvement in post-test performance in both the experimental and comparison groups. While the potential of ACL in second language teaching and learning is undeniable, so are the challenges faced in L2 classrooms. This underscores the need for further empirical research to bridge the gap between theoretical principles and their practical implementation in real classroom settings.

How animal metaphors increase tourists’ waste classification intention?

Abstract Previous researches have shown that animal metaphors play an important role in promoting specific behavioral dispositions of individuals. However, we are not well aware of the role of animal metaphors in tourists' waste classification intentions. Therefore, this study aimed to investigate the impact of animal metaphors advertising for waste classification in scenic spots (vs. non-animal metaphors advertising) on tourists' waste classification intentions. Four experiments (N=1051) were conducted in this study to examine the impacts of animal metaphors advertising in scenic spots, on tourists' waste classification intentions, which enriches the literature on the animal metaphors and tourists' pro-environmental behaviors. The results show that the animal metaphors advertising about waste classification in scenic spots can effectively increase tourists' waste classification intentions. We explored the mediating role of tourists' perceptions of cute animal images in animal metaphors advertising, and the moderating role of visual imagery for animal metaphors advertising, on the relationship between animal metaphors advertising and tourists' waste classification intentions. The results show that there is a significant interaction effect between visual imagery and animal metaphors advertising. In conclusion, this study reveals the different impacts of animal metaphors, cute images and visual imagery on individual tourists, which provides new insights for scenic spot managers to choose waste classification strategies and the looks of bins.

The Experience of Teaching Students to Process and Interpret Tomography Images of Small Laboratory Animals

The Experience of Teaching Students to Process and Interpret Tomography Images of Small Laboratory Animals

ARCHITECTURAL DECORATION ON KHUMS FROM THE MEDIEVAL KAVAT-KALA

Abstract. The article is devoted to the study of ceramic production in the Middle Ages. However, at this stage, attention is focused on the architectural decoration of individual finds from Estate № 2 at Kavat-kala. Khums, as materials for household purposes, have various decorative elements, but the materials available in our case cannot be classified as widespread in terms of ornament and decoration. Some similarities in decoration are found among ceramic (the kashin) products of the Golden Horde period, and are only characteristic of glazed ceramics of the 13th-14th centuries. However, the available information from archaeological excavations at Kavat- kala allows us to judge the most developed forms of pottery production in the 9th-12th centuries. The article also examines the common features of cultural ties in agriculture of the ancient and medieval periods, identifies the cultures of the peoples inhabiting this settlement, and craft production on the basis of unique collected materials from research carried out on the caravan routes of the south of the Right Bank of Khorezm, including the southern and western foothills. Among them, it was established that in one of the medieval estates of Kavat-Kala, near the ancient Russian canal Gavkhor, vessels with richly decorated images of animals of hand-made ceramics have been preserved, dating from the era of the Khorezmshahs (11th-12th centuries) to the era of the Golden Horde (13th - 16th centuries). Today, no less interesting is the arched ornament located along the rims of the hums, which is almost traditional for the Kashin ceramics of the Golden Horde period, on the outside of the vessels.

Exploring post-traumatic stress disorder and trauma in adult animation: a comprehensive analysis of Flee, Waltz witn Bashir and L'Image Manquante

Animation has been employed as a productive and subtle means to represent Post-Traumatic Stress Disorder (PTSD) and historical trauma. The aim of this article is to study the narrative, visual, and psycho-affective strategies of both phenomena through the films Flee (Jonas Poher Rasmussen, 2021), Waltz with Bashir (Ari Folman, 2008), and L'Image Manquante (Rithy Panh, 2013). The ability of animated images to reconstruct moments for which there is no visual testimony, as well as their capacity to evoke the experience of traumatic events, emerges as the center of a specific aesthetic approach to history, forming a type of cinema of the real (Zylberman, 2022). Contrary to the tradition of documentary and visual essay, there is a more frequent expressive use of evocative mechanisms, dreamlike images combined with archival material, and forms of re-enactment of real events that necessarily do not involve the use of actors. The evocation of painful experiences establishes a visual framework in which the viewer becomes the epicenter of the affective staging of trauma and PTSD, prioritizing poetic construction.

Retraction Note: Light image enhancement based on embedded image system application in animated character images

Retraction Note: Light image enhancement based on embedded image system application in animated character images

«ГДЕ ЗАПИСЫВАЮТ В КОШАЧЬИ ИМПЕРАТОРЫ?»: ИСПОЛЬЗОВАНИЕ ОБРАЗОВ ЖИВОТНЫХ В СОВРЕМЕННОМ БРЕНДИРОВАНИИ МУЗЕЕВ И ДОСУГОВЫХ ПРОСТРАНСТВ

The article describes the ways the image of cats is used to make museums attractive to visitors. The author has studied how this practice is applied in such museums as the Hermitage Museum, house museum of Anna Akhmatova on the Fontanka River, the State Museum of Vyborg Castle, and archaeological reserve «Tauric Chersonese». Moreover, some social networking pages on Vkontakte and «Classmates» have been analysed, including those of the cat Bridgelet, the cats from Chersonese, and the cat Philimon from Vyborg Castle. The article proves that the images of the cats from these and other museums have become popular means to attract prospective visitors. The following examples of conducting such a marketing work can prove it: social networking pages run in the name of cats, various contests and events connected with cats. The author has come to the conclusion that the usage of feline images is brought about by multifaceted transformations in society. In particular, nowadays museums and libraries function not merely as places to store data and historically valuable artefacts, but also as leisure facilities. In addition, the attitude to domestic animals plays a huge role here, as now they are kept at home for pleasure, rather than for work. We can’t but mention the changes in the system of social values: domestic asceticism has been replaced by a convenient and cosy way of life, thus popularizing the images of animals that are associated with it.

Disentangling inhibition toward food and non-food stimuli across two hunger levels: An fNIRS study

While individuals tend to display poorer inhibitory control toward food-related than neutral stimuli, it is unclear whether this challenge is specific to food or extends to other pleasant stimuli. Uncertainty also remains regarding the general impact of hunger on inhibition. To address these questions, we used a within-subjects design whereby 44 healthy adults completed two go/no-go tasks including no-go images of highly palatable foods and no-go images of animals matched for valence and physical properties. Both tasks were completed one week apart in either a fed or a fasted state. Prefrontal cortex activity was measured using functional near-infrared spectroscopy. Poorer behavioral inhibition was observed when participants needed to withhold their response to images of food compared to animals, regardless of hunger state. In addition, more commission errors were made in the fasted compared to the fed condition, regardless of the type of image to avoid responding to. Responses to go trials were slower when these trials were interspersed with food compared to animal no-go trials. However, hunger did not influence go response time. Greater activation was observed in the dorsolateral prefrontal cortex during blocks of trials with (vs. without) no-go images, but brain activity did not differ according to the type of no-go image. The effect of hunger on prefrontal brain activity was also not significant. Exploratory correlations showed that food-related inhibition deficits were positively related to self-reported impulsivity, but unrelated to body mass index. This study suggests that even among healthy adults, food-related inhibitory control may have a unique behavioral signature beyond general inhibition toward pleasant stimuli. Hunger also exerts an independent influence on general inhibitory capabilities, highlighting the importance of carefully controlling hunger levels in inhibition studies.

Metadata augmented deep neural networks for wild animal classification

Camera trap imagery has become an invaluable asset in contemporary wildlife surveillance, enabling researchers to observe and investigate the behaviors of wild animals. While existing methods rely solely on image data for classification, this may not suffice in cases of suboptimal animal angles, lighting, or image quality. This study introduces a novel approach that enhances wild animal classification by combining specific metadata (temperature, location, time, etc) with image data. Using a dataset focused on the Norwegian climate, our models show an accuracy increase from 98.4% to 98.9% compared to existing methods. Notably, our approach also achieves high accuracy with metadata-only classification, highlighting its potential to reduce reliance on image quality. This work paves the way for integrated systems that advance wildlife classification technology.