ELTrack: Events-Language Description for Visual Object Tracking by Mohamad Alansari, Khaled Alnuaimi, Sara Alansari, Sajid Javed

“…Additionally, we generate NL descriptions using a Visual-Language (VL) image-captioning module featuring BLIP-2 and GPT-4. These modalities are seamlessly integrated using a superimpose fusion module to enhance tracking performance. …”
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Principles of Organization and Functioning of Mini-CHP Plants Using Local Fuels in Conditions of Hydrogen Energy by R. S. Ignatovich

“…The analysis of literary sources on the current state of development of mini-CHP plants on LF in the structure of the country's energy balance revealed a number of issues related to their operation and construction that arose after the commissioning of the Belarusian NPP. …”
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Weakly Supervised Semantic Segmentation of Remote Sensing Images Using Siamese Affinity Network by Zheng Chen, Yuheng Lian, Jing Bai, Jingsen Zhang, Zhu Xiao, Biao Hou

“…First, we design a seed enhancement module for semantic affinity, which strengthens contextual relevance in the feature map by enforcing a unified constraint principle of cross-pixel similarity, thereby capturing semantically similar regions within the image. …”
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A YOLO11-Based Method for Segmenting Secondary Phases in Cu-Fe Alloy Microstructures by Qingxiu Jing, Ruiyang Wu, Zhicong Zhang, Yong Li, Qiqi Chang, Weihui Liu, Xiaodong Huang

“…Specifically, the EIEM module enhances the C3K2 structure to improve edge perception; the CSPSA module is optimized into C2CGA to strengthen multi-scale feature representation; and the RepGFPN and DySample techniques are integrated to construct the GDFPN neck network. …”
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A Sheep Behavior Recognition Approach Based on Improved FESS-YOLOv8n Neural Network by Xiuru Guo, Chunyue Ma, Chen Wang, Xiaochen Cui, Guangdi Xu, Ruimin Wang, Yuqi Liu, Bo Sun, Zhijun Wang, Xuchao Guo

“…On the one hand, this approach achieves a lightweight model by introducing the FasterNet structure and the selective channel down-sampling module (SCDown). On the other hand, it utilizes the efficient multi-scale attention mechanism (EMA)as well as the spatial and channel synergistic attention module (SCSA) to improve recognition performance. …”
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CGLCS-Net: Addressing Multi-Temporal and Multi-Angle Challenges in Remote Sensing Change Detection by Ke Liu, Hang Xue, Caiyi Huang, Jiaqi Huo, Guoxuan Chen

“…We propose the Context-Aware Global-Local Subspace Attention Change Detection Network (CGLCS-Net) to resolve these issues and introduce the Global-Local Context-Aware Selector (GLCAS) and the Subspace-based Self-Attention Fusion (SSAF) module. …”
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Pilot peer health education for noncommunicable disease prevention in Bangladesh, Ethiopia, and Palau by Lemlem W Gebremariam, Yoshihisa Hirakawa, Shahrin E Rayna, Fahmida A Khan, Chifa Chiang, Yupeng He, Everlynn J Temengil, Sherilynn Madraisau, Md Khalequzzaman, Sohel R Choudhury, Hiroshi Yatsuya, Atsuko Aoyama

“…We developed an education module including role plays and demonstration of sugar amount in popular beverages. …”
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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

“…The key innovation lies in the synergistic integration of several architectural enhancements: the DCNv3_LKA_C2f module, leveraging Deformable Convolution v3 (DCNv3) and Large Kernel Attention (LKA) for better the capture of complex object shapes; an Optimized Feature Pyramid Network structure (Optimized-GFPN) for improved multi-scale feature fusion; the Detect_SA module, incorporating spatial Self-Attention (SA) at the detection head for broader context awareness; and an Inner-Shape Intersection over Union (IoU) loss function to improve bounding box regression accuracy. …”
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Remote Sensing Image Compression via Wavelet-Guided Local Structure Decoupling and Channel–Spatial State Modeling by Jiahui Liu, Lili Zhang, Xianjun Wang

“…It comprises two key modules. The Wavelet Transform-guided Local Structure Decoupling (WTLS) module applies multi-scale wavelet decomposition to disentangle and separately encode low- and high-frequency components, enabling efficient parallel modeling of global contours and local textures. …”
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Hyperspectral Image Super-Resolution via Grouped Second-Order Spatial Features and Spectral Attention Network by Allen Patnaik, M. K. Bhuyan, Sultan Alfarhood, Mejdl Safran

“…We employed a grouped spectral attention (GSA) module to extract spectral details across different bands of HSI images. …”
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RDAU-Net: A U-Shaped Semantic Segmentation Network for Buildings near Rivers and Lakes Based on a Fusion Approach by Yipeng Wang, Dongmei Wang, Teng Xu, Yifan Shi, Wenguang Liang, Yihong Wang, George P. Petropoulos, Yansong Bao

“…To address the above issues, the present study proposes the design of a U-shaped segmentation network of buildings called RDAU-Net that works through extraction and fuses a convolutional neural network and a transformer to segment buildings. …”
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PigFRIS: A Three-Stage Pipeline for Fence Occlusion Segmentation, GAN-Based Pig Face Inpainting, and Efficient Pig Face Recognition by Ruihan Ma, Seyeon Chung, Sangcheol Kim, Hyongsuk Kim

“…PigFRIS employs state-of-the-art occlusion detection with the YOLOv11 segmentation model, a GAN-based inpainting reconstruction module using AOT-GAN, and a lightweight recognition module tailored for pig face classification. …”
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CP-QRRT*: A Path Planning Algorithm for Hyper-Redundant Manipulators Considering Joint Angle Constraints by Tianya Wang, Guoliang Ma, Lisong Xu, Rui Yu

“…Finally, a constraint module designed based on the maximum joint angle constraints of the HRM is implemented to limit the path deflection angles. …”
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THE HISTORICAL PATH OF FORENSIC MEDICINE: FROM LAW TO MEDICINE, FROM MEDICINE TO HIGH TECHNOLOGY by Irina L. Levina, Leonid N. Korol

“…In the structure of the discipline (module) “Forensic Medicine and forensic psychiatry” for students majoring in 40.05.02 – law enforcement, very little time is devoted to the history of forensic medicine, which at all stages of its development is closely connected with the history of law and the development of the world judicial and legal system. …”
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A formally verified authentication protocol in secure framework for mobile healthcare during COVID-19-like pandemic by Shaik Shakeel Ahamad, Al-Sakib Khan Pathan

“…In addition to these issues, mobile healthcare applications are prone to various types of attacks and formal proof is often unavailable. …”
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Small sample data pricing research based on Reptile algorithm by Junxin Shen, Yi Yang, Fanghao Xiao

“…The methods proposed in this research are universally applicable for addressing the small sample problem in data pricing, providing a reference for solving similar issues. …”
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Computing Legal Analysis: A Guided Approach to Problem Solving in Contract Law by Marton Ribary, Antony Starza-Allen

“…The method creates scaffolding for learning and a framework through which legal issues can be identified. These frameworks can be used to locate legal information relevant to the construction of analysis and argument to the point of producing legal advice with confidence. …”
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vFerryman: An Artificial Intelligence-Driven Personalized Companion Providing Calming Visuals and Social Interaction for Emotional Well-Being by Wei-Ji Wang

“…As awareness of mental health issues grows, there is an increasing demand for innovative tools that provide personalized emotional support. …”
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Towards real-world monitoring scenarios: An improved point prediction method for crowd counting based on contrastive learning. by Rundong Cao, Jiazhong Yu, Ziwei Liu, Qinghua Liang

“…Additionally, a multi-scale feature fusion module is proposed to obtain high-quality feature maps for detecting targets of different scales. …”
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EEG emotion recognition based on parallel separable convolution and label smoothing regularization by Yong ZHANG, Jikui LIU, Wenlong KE

“…In recent years, emotion recognition methods based on deep learning and electroencephalogram (EEG) have achieved good results.However, existing methods still have issues such as incomplete extraction of emotional features from EEG and significant impact from artificially mislabeled emotional labels.A parallel separable convolution and label smoothing regularization (PSC-LSR) network model was proposed.Firstly, through the attention mechanism, EEG important time points and important channels were given greater weight to obtain shallow emotional features of EEG.Secondly, a parallel separable convolution module was used to comprehensively extract EEG emotional information and obtain deep emotional features.Finally, the emotion label smoothing regularization method was used to optimize the model parameters, which increased model’s fault tolerance probability for incorrect labels, enhanced the generalization and robustness of the network model, and improved accuracy of EEG emotion recognition.The proposed method has been validated in two datasets, in which the average accuracy rates of arousal and valence dimensions in the DEAP dataset reaches 99.23% and 99.13%, respectively.In the Dreamer dataset, the average accuracy rates for both arousal and valence dimensions reaches 97.33% and 97.25%.…”
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