TPL-DA: A Novel Threshold-Free Pseudolabel Learning Framework for Domain Adaptive Semantic Segmentation of High-Resolution Remote Sensing Images by Yan Ren, Jie Long, Xiaowen Gao, Ming Zhang, Guoqing Liu, Nan Su

“…In the ST stage, we propose a dynamic threshold-free pseudolabel learning strategy that utilizes well-aligned feature prototypes in the feature space to guide pseudolabel generation in the probability space, eliminating the threshold constraints. …”
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An Adaptive Obstacle Avoidance Model for Autonomous Robots Based on Dual-Coupling Grouped Aggregation and Transformer Optimization by Yuhu Tang, Ying Bai, Qiang Chen

“…This method employs a Transformer-based dual-coupling grouped aggregation strategy to optimize feature extraction and improve global feature representation, allowing the model to capture both local and long-range dependencies. …”
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Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders by Hui Yang, Walid Aydi, Nisreen Innab, Mohamed E. Ghoneim, Massimiliano Ferrara

“…In the third phase, cervical cancer images are segmented using the Seg-UNet model, which is forwarded to the feature extraction phase that employs denoising autoencoders. …”
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A review of deep-learning-based models for afaan oromo fake news detection on social media networks by Kedir Lemma Arega, Kula Kekeba Tune, Asrat Mulatu Beyene, Wegderes Tariku, Nurhussen Menza Bune

“…The findings suggest the need for specialized datasets and advanced models to mitigate fake news spread and enhance information credibility.…”
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RMIS-Net: a fast medical image segmentation network based on multilayer perceptron by Binbin Zhang, Guoliang Xu, Yiying Xing, Nanjie Li, Deguang Li

“…This architecture achieves significant parameter reduction while enhancing local feature representation through optimized shift operations. …”
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Real-Time Detection of Varieties and Defects in Moving Corn Seeds Based on YOLO-SBWL by Yuhang Che, Hongyi Bai, Laijun Sun, Yanru Fang, Xinbo Guo, Shanbing Yin

“…At the neck of the network, the path-aggregation feature pyramid network was replaced with the weighted bi-directional feature pyramid network (BiFPN) to increase the accuracy of classifying undamaged corn seeds. …”
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Research into Robust Federated Learning Methods Driven by Heterogeneity Awareness by Junhui Song, Zhangqi Zheng, Afei Li, Zhixin Xia, Yongshan Liu

“…First, a heterogeneity quantification mechanism is designed based on statistical feature distributions, enabling the effective measurement of inter-client data discrepancies. …”
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A Hybrid Deep Multistacking Integrated Model for Plant Disease Detection by Majdi Khalid, MD. Alamin Talukder

“…Therefore, accurate and efficient models for timely identification and mitigation are imperative to address these challenges and ensure sustainable agricultural practices. …”
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An explainable AI-driven transformer model for spoofing attack detection in Internet of Medical Things (IoMT) networks by Mohammad A. Alsharaiah, Mohammed Amin Almaiah, Rami Shehab, Mansour Obeidat, Fuad Ali El-Qirem, Theyazn Aldhyani

“…The core of our novel model is a Transformer neural network, enhanced with a custom attention mechanism to improve feature extraction and classification accuracy. To enhance model interpretability and foster trust in AI-driven security systems, we integrate Explainable AI (XAI) techniques, specifically SHAP analysis, allowing for a deeper understanding of feature contributions in decision-making. …”
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Edge–Cloud Intelligence for Sustainable Wind Turbine Blade Transportation: Machine-Vision-Driven Safety Monitoring in Renewable Energy Systems by Yajun Wang, Xiaodan Wang, Yihai Wang, Shibiao Fang

“…It is enhanced with convolutional block attention modules (CBAMs) for feature refinement, CARAFE upsampling for better contextual detail, and bidirectional feature pyramid networks (BiFPNs) for multi-scale object detection. …”
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Tunnel water inflow prediction using explainable machine learning and augmented partially missing dataset by Shengdong Ju, Guangzhao Ou, Tao Peng, Yanning Wang, Quanlin Song, Peng Guan

“…The proposed BO-XGBoost model exhibited exceptionally high predictive accuracy on the tunnel water inrush volume prediction dataset, thereby aiding managers in making informed decisions to mitigate water inrush risks and ensuring the safe and efficient advancement of tunnel projects.…”
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Autonomous novel class discovery for vision-based recognition in non-interactive environments by Xuelin Zhang, Feng Liu, Xuelian Cheng, Siyuan Yan, Zhibin Liao, Zongyuan Ge

“…To address the OSC problem, we propose a framework combining three approaches: 1) using selfsupervised vision transformers to mitigate the discard of information needed for clustering unknown classes; 2) adaptive weighting for image patches to prioritize patches with richer textures; and 3) incorporating a temperature scaling strategy to generate more separable feature embeddings for clustering. …”
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Evaluating metaheuristic solution quality for a hierarchical vehicle routing problem by strong lower bounding by Marduch Tadaros, Athanasios Migdalas, Nils-Hassan Quttineh, Torbjörn Larsson

“…In both of these the computational complexity is mitigated through an enumeration of the switch point options. …”
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Audio Deepfake Detection: What Has Been Achieved and What Lies Ahead by Bowen Zhang, Hui Cui, Van Nguyen, Monica Whitty

“…The survey then delves into detection approaches, covering frontend feature extraction, backend classification models, and end-to-end systems. …”
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Regulation of enzymatic lipid peroxidation in osteoblasts protects against postmenopausal osteoporosis by Qiong-Yi Zhang, Hai-Biao Gong, Man-Ya Jiang, Fujun Jin, Guan Wang, Chang-Yu Yan, Xiang Luo, Wan-Yang Sun, Shu-Hua Ouyang, Yan-Ping Wu, Wen-Jun Duan, Lei Liang, Yun-Feng Cao, Xin-Xin Sun, Meijing Liu, Gen-Long Jiao, Hua-Jun Wang, Kurihara Hiroshi, Xiaogang Wang, Rong-Rong He, Yi-Fang Li

“…Our study identifies phospholipid peroxidation in osteoblasts as a key feature of postmenopausal osteoporosis. Estrogen regulates the transcription of glutathione peroxidase 4 (GPX4), an enzyme crucial for reducing phospholipid peroxides in osteoblasts. …”
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Spatial-Temporal Sequence Attention Based Efficient Transformer for Video Snow Removal by Tao Gao, Qianxi Zhang, Ting Chen, Yuanbo Wen

“…Furthermore, we introduce the concept of Neural Representation for Videos (NeRV) and effectively reconstruct compressed videos after multi-resolution feature extraction using the recovery NeRV module, thereby further reducing computational consumption. …”
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Unsupervised Domain Adaptation Method Based on Relative Entropy Regularization and Measure Propagation by Lianghao Tan, Zhuo Peng, Yongjia Song, Xiaoyi Liu, Huangqi Jiang, Shubing Liu, Weixi Wu, Zhiyuan Xiang

“…This paper presents a novel unsupervised domain adaptation (UDA) framework that integrates information-theoretic principles to mitigate distributional discrepancies between source and target domains. …”
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Hybrid Android Malware Detection and Classification Using Deep Neural Networks by Muhammad Umar Rashid, Shahnawaz Qureshi, Abdullah Abid, Saad Said Alqahtany, Ali Alqazzaz, Mahmood ul Hassan, Mana Saleh Al Reshan, Asadullah Shaikh

“…Unlike prior approaches, the proposed system integrates a multi-dimensional analysis of Android permissions, intents, and API calls, enabling robust feature extraction even under reverse engineering constraints. …”
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A Numerical Study on the Crashworthiness of Corrugated Conical Tubes with Small Semi-Apical Angles and Their Influence Mechanism by Yiheng Song, Qinyu Lin, Jinxiang Chen, Tidong Zhao

“…To develop a new type of biomimetic single-cell and multi-cell energy-absorbing box (tube) featuring conical tubes at the intersection of cell walls, it is necessary to address the issue of large bottom-space requirements in current conical energy-absorbing tubes with superior crashworthiness due to their large semi-apical angles. …”
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Enhancing Business Success Prediction: A Data-Driven Machine Learning Mode by Deo Arpit, Korde Manish, Tiwari Anant, Jain Anant, Choudhary Akash

“…Data preprocessing methods, including outlier detection, feature selection, and dimensionality reduction, improve model accuracy. …”
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