Holistic Image Research Articles

Length of Stay and Destination Image: Insights from Social Media Content of Day Trippers and Tourists

ABSTRACT Social media platforms have a significant role in determining destination image. This study examines the impact of length of stay on destination image as reflected on visitors’ posts on social media through a comparative analysis of day trippers and tourists. Two text mining methods (Term Frequency-Inverse Document Frequency and Latent Dirichlet Allocation) and an image classification model (ResNet) were applied to Weibo data to identify day trippers’ and tourists’ online destination image. Differences were found between day trippers and tourists when examining keywords, topics, and visual scenes. The keyword-based image was predominantly utilitarian for day trippers and more recreational-oriented for tourists. Moreover, tourists shared a greater variety of topic-based image attributes (e.g. accommodation, catering, activity) than day trippers, and form an abundant holistic image. Both groups were highly consistent in the visual category of common images and top-10 visual scenes of unique features, though significant differences were recorded when considering gender.

Semantic Interaction Meta-Learning Based on Patch Matching Metric.

Metric-based meta-learning methods have demonstrated remarkable success in the domain of few-shot image classification. However, their performance is significantly contingent upon the choice of metric and the feature representation for the support classes. Current approaches, which predominantly rely on holistic image features, may inadvertently disregard critical details necessary for novel tasks, a phenomenon known as "supervision collapse". Moreover, relying solely on visual features to characterize support classes can prove to be insufficient, particularly in scenarios involving limited sample sizes. In this paper, we introduce an innovative framework named Patch Matching Metric-based Semantic Interaction Meta-Learning (PatSiML), designed to overcome these challenges. To counteract supervision collapse, we have developed a patch matching metric strategy based on the Transformer architecture to transform input images into a set of distinct patch embeddings. This approach dynamically creates task-specific embeddings, facilitated by a graph convolutional network, to formulate precise matching metrics between the support classes and the query image patches. To enhance the integration of semantic knowledge, we have also integrated a label-assisted channel semantic interaction strategy. This strategy merges word embeddings with patch-level visual features across the channel dimension, utilizing a sophisticated language model to combine semantic understanding with visual information. Our empirical findings across four diverse datasets reveal that the PatSiML method achieves a classification accuracy improvement of 0.65% to 21.15% over existing methodologies, underscoring its robustness and efficacy.

Multi-Stage Frequency Attention Network for Progressive Optical Remote Sensing Cloud Removal

Cloud contamination significantly impairs optical remote sensing images (RSIs), reducing their utility for Earth observation. The traditional cloud removal techniques, often reliant on deep learning, generally aim for holistic image reconstruction, which may inadvertently alter the intrinsic qualities of cloud-free areas, leading to image distortions. To address this issue, we propose a multi-stage frequency attention network (MFCRNet), a progressive paradigm for optical RSI cloud removal. MFCRNet hierarchically deploys frequency cloud removal modules (FCRMs) to refine the cloud edges while preserving the original characteristics of the non-cloud regions in the frequency domain. Specifically, the FCRM begins with a frequency attention block (FAB) that transforms the features into the frequency domain, enhancing the differentiation between cloud-covered and cloud-free regions. Moreover, a non-local attention block (NAB) is employed to augment and disseminate contextual information effectively. Furthermore, we introduce a collaborative loss function that amalgamates semantic, boundary, and frequency-domain information. The experimental results on the RICE1, RICE2, and T-Cloud datasets demonstrate that MFCRNet surpasses the contemporary models, achieving superior performance in terms of mean absolute error (MAE), root mean square error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity index (SSIM), validating its efficacy regarding the cloud removal from optical RSIs.

Infrared thermogram image guided discontinuous appearances of hyaluronic acid for classification of arthritic knee joints

The liveliness of a human potentially depends on his/her smooth movability. To accomplish the work of daily life, the joints of the body need to be healthy. However, the occurrence of Rheumatoid arthritis and Osteoarthritis has a significant prevalence towards the immovability of humankind. Rheumatoid arthritis (RA) and Osteoarthritis (OA) mostly affect the joints of the hand and knee which result in lifelong pain, inability to climb, walk, etc. In the early stages, these diseases attack the synovial membrane and synovial fluid, and further it destroys the soft tissues and bone structure. By early diagnosis, we can start the treatment in the early stage which may cure these diseases with such extreme consequences. As per clinical studies of previous literature, it is observed that synovial fluid imbalance appears in the early stage of such diseases and Hyaluronic Acid (HA) concentration also decreases for that. Therefore, estimation of HA is a significant key to arthritis disease classification and grading. In this paper, we proposed a hybrid framework for classification of arthritic knee joints based on the analysis of the discontinuous appearances of the HA concentration using infrared imaging technology. To meet up the specific necessities, firstly we have proposed a modified K-Means clustering algorithm for extraction of the region of interest (ROI) i.e., the knee joint surface. Secondly, a mathematical formulation is proposed to calculate the concentration of HA from the segmented ROIs. This experimental process was implemented on the publicly available IR (Infrared) Knee Joint Dataset and for further evaluation of the novelty of mathematical formulation, we have extended the proposed work to the classification of healthy and arthritis affected knee joints depending on significant discriminative characteristics of the HA concentration with respect to the existing significant imaging features. Experimental results and analysis demonstrates that concentration of HA has the dominant potential for classifying healthy and arthritic knee joints using infrared holistic images. Our experimental analysis reveals that estimation and combination of the HA concentration features with conventional handcrafted and deep features increases the classification performance with an average accuracy of 91% and 97.22% respectively as compared to the each individual feature sets.

Omnidirectional image quality assessment with local–global vision transformers

With the rising popularity of omnidirectional images (ODIs) in virtual reality applications, the need for specialized image quality assessment (IQA) methods becomes increasingly critical. Traditional IQA approaches, designed for rectilinear images, often fail to evaluate ODIs accurately due to their 360-degree scene representation. Addressing this, we introduce the Local–Global Transformer for 360-degree Image Quality Assessment (LGT360IQ). This novel framework features dual branches tailored to mimic top-down and bottom-up visual attention mechanisms, adapted for the spherical characteristics of ODIs. The local branch processes tangent viewports from salient regions within the equirectangular projection image, extracting detailed features for granular quality assessment. In parallel, the global branch utilizes a task-dependent token sampling strategy for holistic image feature processing and quality score prediction. This integrated approach combines local and global information, offering an effective IQA method for ODIs. Our extensive evaluation across three benchmark ODI datasets, CVIQ, OIQA, and ODI, demonstrates LGT360IQ superior performance and establishes its role in advancing the field of IQA for omnidirectional images.

Assembling Cities in Contemporary Discursive Practices

The article presents issues that reflect modern strategies and tactics for constructing a holistic image of a city. The so-called assembly (reassembly) is executed in response to the challenges of a scattered, fragmented, decentralized, hybrid city, but a developing city nonetheless. We reveal several types of “assembly”, depending on who the “outlook collectors” are: each time these are either those who generally approve of the policies of the powers that be, or opposition-minded bloggers, popular leaders of urban communities; or members of research groups. The authors consider the city as a dynamic system that forms many vectors of development and makes for diversity of urban discourse. The article proves that in the media three types of discourse compete in the city space: the discourse of sustainable development, critical urbanism, as well as a softer version referred to as the discourse of new urbanism. We conduct subject analysis of texts and statements made by members of social media communities (from three Siberian cities: Novosibirsk, Barnaul, Tomsk), who conduct spatial development audits and offer their own scenarios for putting together a city. The role and the importance are shown of virtual assemblies, which, if social media communities are anything to go by, can lead to creating actual assemblies and to the interaction of all city actors in the process of transforming space, to revising the modes of involvement of citizens in process of designing urban life. Discussions related to putting together a city may also slow down the process of implementing urban projects and hamper practices of further developing cities that are considered historical settlements. Moreover, citizens’ demands for an authentic urban space that can be called genuine and historic are often neglected by government officials. Each of the analyzed cities demonstrates its own unique set of institutional mechanisms and interactions of participants in decision-making arenas that are a product of a certain unique cultural, social, political and historical context.

“Mental map” in “Letters of a Russian Traveler” by Nikolay Karamzin and the problem of the national myth representation

The article analyzes “Letters of a Russian Traveler” by Nikolay Karamzin in terms of the symbolic-mythological perception of space, suggesting a view of the countries, depicted in the travelogue, as symbolic-mythological units of the “mental map” in the book. A “mental map” is understood as a holistic image of a geographical space, value-restructured in accordance with the author’s vision of European cultural and the historical situation. The purpose of the work is to reveal the hidden additional plot of Karamzin’s book, which determines the logic of the perception of geographical space and its comprehension, taking into account the historical and political situation witnessed by Karamzin’s hero-traveler. Using the methodology of the structural-semiotic, historical-genetic and comparative-typological reading of the text, as well as the methodology of human geography, the article shows how Karamzin generalizes ideas about the logic of the Western European history and culture development at the end of the 18th century. We also characterize the writer’s symbolic and mythological view of the cultural dialogue between Russia and Europe, the place and role of the “Letters...” of France, Switzerland, England and the countries of the German world on the “mental map”. Conclusions are drawn about the significance of the spatial image of “Letters...” for the design of Karamzin’s historical and political concept of the late 18th century, in which the key role was played by the ideas of the dialogue, the ability to evaluate the achievements of European culture and to develop the potential of Russian culture.

THE ROLE OF INTER-SUBJECT INTEGRATION IN THE EDUCATIONAL PROCESS

The article explores the principle of interdisciplinary communication. The role of integration in creating a holistic and indivisible image of the world is clarified in the minds of students. General concepts, categories and approaches related to understanding are classified. It is noted that integration contributes to the formation of different types of knowledge. It is emphasized that teaching similar and complementary topics in different subjects at the same level will give students more comprehensive knowledge.

THE USEFULNESS OF BRANDING IN AGRICULTURAL MARKETING

The post-pandemic landscape has ushered in significant changes in food and agricultural markets, with a call from policymakers for proactive transformation towards a climate-neutral, digital, and inclusive food sector. Despite policy recommendations, market trends are primarily shaped by consumer behaviour, and many consumers remain hesitant to embrace circular economy practices and sustainability paradigms. Thus, policymakers must consider consumer preferences and willingness to change consumption patterns. In this context, branding emerges as a crucial tool in agricultural marketing, capable of influencing consumer preferences and promoting agricultural products, contributing to the sector's overall success. A traditional view of agricultural marketing involves the logistics of moving products from farms to consumers. However, in this evolving landscape, branding transcends mere logos and slogans, encompassing the holistic image, reputation, and perception of agricultural products. This article explores the role of branding within the agricultural supply chain and delves into the importance of branding by examining strategies and case studies in agricultural markets. It also underscores the challenges in agricultural branding while offering potential solutions.

Graph Representation and Prototype Learning for webly supervised fine-grained image recognition

Webly supervised fine-grained image recognition (FGIR) learns to distinguish sub-ordinate categories based on webly-retrieved data, which can dramatically alleviate the dependency on manually annotated labels. This is quite a challenging task due to the heavy noise labels and the inherent dilemma of small inter-class variance and large intra-class variance. Current webly supervised algorithms learn holistic category prototypes to help correct noisy labels but ignore local features that can distinguish different sub-ordinate categories. In this work, we propose a Graph Representation and Prototype Learning (GRPL) framework to automatically mine discriminative local regions and their interactions with holistic image to learn instance graph representation both category graph prototype to help correct noisy labels and retrieve out-of-distribution (OOD) samples. Specifically, an attention-focused module is designed to extract the discriminative regions and then build a structured graph to correlate them with the holistic image for each instance and an identical graph to model holistic-local correlations for each category. Next, we apply two stacked graph convolution networks to explore holistic-local interaction within each graph and across two graphs to learn graph representation for each instance and graph prototype for each category. Finally, the similarities between the instance-level and prototype-level graph representation are learned to help correct noisy labels and exclude OOD samples. Extensive experiments conducted on several datasets show the proposed approach achieves superior performance compared with current leading algorithms.

Masked autoencoders with generalizable self-distillation for skin lesion segmentation.

In the field of skin lesion image segmentation, accurate identification and partitioning of diseased regions is of vital importance for in-depth analysis of skin cancer. Self-supervised learning, i.e., MAE, has emerged as a potent force in the medical imaging domain, which autonomously learns and extracts latent features from unlabeled data, thereby yielding pre-trained models that greatly assist downstream tasks. To encourage pre-trained models to more comprehensively learn the global structural and local detail information inherent in dermoscopy images, we introduce a Teacher-Student architecture, named TEDMAE, by incorporating a self-distillation mechanism, it learns holistic image feature information to improve the generalizable global knowledge learning of the student MAE model. To make the image features learned by the model suitable for unknown test images, two optimization strategies are, Exterior Conversion Augmentation (EC) utilizes random convolutional kernels and linear interpolation to effectively transform the input image into one with the same shape but altered intensities and textures, while Dynamic Feature Generation (DF) employs a nonlinear attention mechanism for feature merging, enhancing the expressive power of the features, are proposed to enhance the generalizability of global features learned by the teacher model, thereby improving the overall generalization capability of the pre-trained models. Experimental results from the three public skin disease datasets, ISIC2019, ISIC2017, and PH indicate that our proposed TEDMAE method outperforms several similar approaches. Specifically, TEDMAE demonstrated optimal segmentation and generalization performance on the ISIC2017 and PH datasets, with Dice scores reaching 82.1% and 91.2%, respectively. The best Jaccard values were 72.6% and 84.5%, while the optimal HD95% values were 13.0% and 8.9%, respectively.

СПОСОБЫ РЕПРЕЗЕНТАЦИИ НЕВЕРБАЛЬНЫХ КОМПОНЕНТОВ ОБЩЕНИЯ В ПОВЕСТИ А. П. ЧЕХОВА «СТЕПЬ»

The dialogical fragment of text is a part of prose fiction, where responses (characters’ speech) and remarks (author’s speech) represent the communication between characters. The characters’ dialogue may include the description of nonverbal components that make fictional dialogue closer to the natural one due to the constant presence of nonverbal components in the oral communication. In this article the ways of including the nonverbal components of characters' communication have been analyzed. The remarks accompanying the characters’ words may be placed in the different parts of dialogue according to the characters’ responds. The nonverbal components are more often included in the interpositive and postpositive remarks and are located after the verb with the meaning of the speaking process which is obligatory for the structure of the remark. The verbs, gerunds, verb and noun phrases represent the nonverbal components in the text. The remarks that accompany the characters’ speech of the dialogical fragments of text represent the characters’ emotional state and feelings (laughter, crying, wonder, joy, dryness, contempt). In the work the description of the nonverbal components that accompany the characters’ speech may be correlated with the author’s description of the character out of the communication. It contributes to the creation of the holistic artistic images. Key words: dialogical fragment of text, response, remark, nonverbal components, images of characters

Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification

Occluded person re-identification (Re-ID) aims to address the potential occlusion problem when matching occluded or holistic pedestrians from different camera views. Many methods use the background as artificial occlusion and rely on attention networks to exclude noisy interference. However, the significant discrepancy between simple background occlusion and realistic occlusion can negatively impact the generalization of the network. To address this issue, we propose a novel transformer-based Attention Disturbance and Dual-Path Constraint Network (ADP) to enhance the generalization of attention networks. Firstly, to imitate real-world obstacles, we introduce an Attention Disturbance Mask (ADM) module that generates an offensive noise, which can distract attention like a realistic occluder, as a more complex form of occlusion. Secondly, to fully exploit these complex occluded images, we develop a DualPath Constraint Module (DPC) that can obtain preferable supervision information from holistic images through dualpath interaction. With our proposed method, the network can effectively circumvent a wide variety of occlusions using the basic ViT baseline. Comprehensive experimental evaluations conducted on person re-ID benchmarks demonstrate the superiority of ADP over state-of-the-art methods.

MP2PMatch: A Mask-guided Part-to-Part Matching network based on transformer for occluded person re-identification

Occluded person re-identification (ReID) remains challenging due to the misaligned body parts. Existing works, mainly utilizing extra clues, excel in predicting holistic person images but falter when confronting substantial occlusion. This paper proposes a transformer-based Mask-guided Part-to-Part Matching (MP2PMatch) network for fine-grained matching. Firstly, the Consistency Occlusion Augmentation (COA) processes holistic person images and corresponding body part masks to construct occluded “image-mask” pairs. Next, we introduce learnable part tokens to capture semantic features of various body parts, performing “pull close” and “push apart” operations based on identity labels and part visibility, ensuring the one-to-one correspondence between part features and body parts. Additionally, the proposed Body Region Attention (BRA) utilizes the overall attention on body regions to guide the network to overcome interference from both occlusion and background. Extensive experiments demonstrate that MP2PMatch achieves exceptional occluded ReID performance.

Support of Cancer Patients at the Stage of Early Rehabilitation: Possibilities of Postural Correction and Art Therapy Techniques

Introduction. Early rehabilitation of cancer patients after surgery plays an important role in their recovery and return to normal functioning. One of the tasks of this stage of treatment is to restore physical activity of the body, in particular, through postural correction. The medical aspects of this process are well described in the literature, however, the psychological aspects of the postural correction process are not sufficiently covered. Even fewer studies are devoted to restoring the psychological state of cancer patients. Purpose. Analysis of the possibilities of postural correction of cancer patients and the possibility of using art therapy techniques to normalize the psychological state during early rehabilitation.Theoretical justification. One of the key elements of postural correction is the restoration of the ability to maintain balance. For this purpose, special devices are used – stabilometric platforms. Another important element is the restoration of voluntary movements. For a more effective recovery, it is worth teaching patients the psychological adjustment to exercise movements. When the patient plans a movement, he forms a mental construct “task to be completed”, which promotes more precise movements. Restoration of their stable psychological state of cancer patients is possible, in particular, through art therapy techniques. One of the techniques, coloring mandalas, involves both hemispheres of the patients’ brains, triggering cognitive processes through the activation of fine motor skills. This provides a natural therapeutic process: the brain works initially on simple tasks and gradually moves on to more complex ones. The details of the mandala drawing are thought out in such a way that in the process of working on it, the patient focuses on his inner state – thoughts and feelings.Discussion. The importance of an integrated approach to the rehabilitation of cancer patients is increasingly emphasized in scientific papers. During the early rehabilitation period, the patient is in the most vulnerable state, both physically and psychologically. The use of psychological techniques can ensure that the patient can restore a more holistic image of himself both physically and internally.

Digital Channels of Employer Brand Formation

Relevance. In modern conditions of high competition in the labor market, new forms of work are becoming particularly relevant, in particular, the creation of an HR brand as a tool for maintaining the company's image and attracting employees. The development of digital technologies has allowed companies to use new channels of employer brand formation – digital. However, despite the existing need, the features of their use have not been fully studied. Social networks and career sites as the main platforms for the formation of an employer's brand are rapidly developing and transforming, which requires their comprehensive research. The purpose is to identify the features of the use of career sites and social networks as the main digital channels for the formation of an employer's brand. Objectives: to reveal the essence and identify the main elements of the employer's brand; to conduct a comparative study of the use of career sites and social networks of four Russian companies: Dodo Pizza, Gulfstream, Chulakov.ru, Exness. Methodology. The methodological basis of the study was the work of G. Martin, S. Hat Trick, T. Ambler, S. Burrow. As a technical tool for the study of social networks, the system of multifactorial analysis of social media "Cribrum" was used, the method of content analysis was used in the study of career websites of companies. Results. As a result of the study, the authors identified the main components of the HR brand broadcast by digital channels focused on basic and additional values. The analysis of digital channels by selected elements revealed the specifics of their use in the formation of the employer's brand. Career sites to a greater extent broadcast additional values of the company, forming a holistic positive image for the general public, without highlighting the target categories of recruiting. Social networks mainly demonstrate the basic values of the company, their content is more specific, focused on certain categories of recruiting. Conclusion. Creating a successful employer brand requires a competent combination of the digital channels considered, taking into account their specifics and the category of recruiting, which will allow HR branding to become a long-term HR strategy for attracting and retaining target groups of employees.

Deep learning-based fusion networks with high-order attention mechanism for 3D object detection in autonomous driving scenarios

In the realm of autonomous driving, accurately detecting 3D objects is both vital and challenging. Recently, deep convolutional networks have been successfully implemented in the fusion of LiDAR and camera data, delivering impressive results. However, prevailing approaches tend to concentrate on basic architectural designs and the use of fixed 3D bounding boxes, overlooking the exploration of feature interrelations and the varying scales of 3D objects. In this paper, we propose High-order Attention Mechanism Fusion Networks (HAMFNs) for image expression and multi-scale learning, based on a novel high-order attention mechanism with multi-scale detection and scale linear regression. High-order convolution layers are built for tenser filtering with discriminative representations of the holistic image. Multi-scale query module further characterizes the saliency properties of the 3D objects. Our tests on the nuScenes dataset show that HAMFNs outperform the latest top-performing methods, achieving a 0.7% increase in mean Average Precision (mAP). We further integrated high-order convolutional layers into ResNet-50, ResNet-101, and ResNet-152 architectures, enhancing their performance with minimal parameter increase. The Top-1 error rates were reduced by 1.65%, 1.63%, and 1.60% for each network, respectively.

КАТЕГОРИИ МУЗЫКАЛЬНОГО И ВИЗУАЛЬНОГО В СЮЖЕТЕ СТИХОТВОРЕНИЯ Ю. ЛЕВИТАНСКОГО "КАК ПОКАЗАТЬ ОСЕНЬ"

The article is about the categories of musical and visual in Yu. Levitansky’s poem “How to show autumn” (Cinematograph, 1970). The text clearly shows the connection between these categories, as well as their role in the construction of artistic reality and the plot of the poem. In turn, the functions of the musical are considered, namely how sound can influence the organization of the figurative system, visual perception and also how the musical becomes visible. The article shows how the categories of musical and visual become inseparable components of the artistic world and build its holistic image

ОБРАЗ НАСТОЯЩЕГО И БУДУЩЕГО В ПРЕДСТАВЛЕНИЯХ ПРИЕМНЫХ РОДИТЕЛЕЙ

Parenting is considered from the point of view of the co-being approach, which allows studying the family in the coordinates of: jointness, space and time. The conceptual model of adaptive parenting activity is presented, the sustainability of which is determined by the time perspective, including perceptions of interaction in the dyad “adaptive parent-adaptive child”. The purpose of the study was to examine adaptive parents' perceptions of time perspective. Forty adaptive parents (20 females and 20 males) and 41 biological parents (19 females and 22 males) participated in the study. To achieve the purpose of the study, the Motivational Inductors Method of J. Nütten in adaptation of A. D. Leontiev was used. The results revealed the peculiarities of adaptive parents' perspective on the future in comparison with biological parents, the former group relies predominantly on the near future. In the open present, adaptive parentstend toexpress orientation to psychological self-preservation, egoism, maximum aspiration and dissatisfaction with the state of affairs. In the near-term perspective, adaptive parents express the aspiration for the development of abilities, cognition and interest, in contrast to biological parents, focused to their professional activity and the child's studies. In the long term, adaptive parents are dominated by the importance of cognition and interest, achievement motivation, activity, orientation to learning activities (their own and the child's), while the biological parents' orientation to the child, to the development of character, personality traits, abilities and learning activities increases. Conclusions were drawn about adaptive parents' representation of the adaptive family image and the presence of a delayed life script. It was suggested that adaptive parents should be trained with emphasis on the development of skills of building a future perspective and the formation of a holistic image of their activities.

ВИКОРИСТАННЯ МЕТОДІВ БРЕНД- І PR-МЕНЕДЖМЕНТУ В РЕГІОНАЛЬНОМУ ТУРОПЕРЕЙТИНГУ

The article examines modern methods of brand and PR management and their application in the context of regional tour operating. Brand management is an important tool for increasing the recognition and attractiveness of a tourist product. This includes creating a unique image that distinguishes a certain tourist destination or service from competitors. A successful brand helps to create an emotional connection with the target audience, which contributes to the growth of loyalty and long-term relationships with customers. PR management in tour operating is aimed at managing public opinion and forming a positive image of the region as a tourist destination. This is achieved through active interaction with the mass media, holding press conferences, participation in tourist exhibitions, organization of information tours for journalists and bloggers. An important aspect is also the management of crisis situations and the minimization of the negative impact of unforeseen events on the reputation of the region. Regional tour operating focused on a specific geographic area has its own specific challenges and advantages. One of the main tasks is the formation of a holistic image of the region, which includes cultural, historical and natural features. An important role is played by cooperation with local authorities, enterprises and public organizations, which allows for the creation of complex tourist products. Effective use of brand and PR strategies helps to attract more tourists, increase the competitiveness of the region and increase income from tourism. It is also important to take into account current trends and innovations in marketing, such as the use of digital platforms, social networks and influencers. The article analyzes specific examples of the successful application of brand and PR management in different regions of the world, which allows to determine the best practices and adapt them to the conditions of domestic tour operating. Particular attention is paid to methods of measuring the effectiveness of brand and PR campaigns, which allows us to assess their impact on the development of regional tourism. In addition, the prospects for the development of brand and PR management in the conditions of globalization and digital transformation are considered. Attention is paid to the role of technologies in the creation of interactive content, virtual tours and other innovative approaches that make the tourist product more attractive to the modern consumer. In general, the article emphasizes the importance of an integrated approach to the use of brand and PR management methods in regional tour operating, which is a key success factor in conditions of high competition in the tourism market.