Visual explanation method for reversible neural networks by Xinying MU, Bingbing SONG, Fanxiao LI, Yisen ZHENG, Wei ZHOU, Yunyun DONG

“…The issue of model explainability has gained significant attention in understanding the vulnerabilities and anonymous decision-making processes inherent in deep neural networks (DNN).While there has been considerable research on explainability for traditional DNN, there is a lack of exploration on the operation mechanism and explainability of reversible neural networks (RevNN).Additionally, the existing explanation methods for traditional DNN are not suitable for RevNN and suffer from issues such as excessive noise and gradient saturation.To address these limitations, a visual explanation method called visual explanation method for reversible neural network (VERN) was proposed for RevNN.VERN leverages the reversible property of RevNN and is based on the class-activation mapping mechanism.The correspondence between the feature map and the input image was explored by VERN, allowing for the mapping of classification weights of regional feature maps to the corresponding regions of the input image.The importance of each region for model decision-making was revealed through this process, which generates a basis for model decision-making.Experimental comparisons with other explanation methods on generalized datasets demonstrate that VERN achieves a more focused visual effect, surpassing suboptimal methods with up to 7.80% improvement in average drop (AD) metrics and up to 6.05% improvement in average increase (AI) metrics in recognition tasks.VERN also exhibits an 82.00% level of localization for the maximum point of the heat value.Furthermore, VERN can be applied to explain traditional DNN and exhibits good scalability, improving the performance of other methods in explaining RevNN.Furthermore, through adversarial attack analysis experiments, it is observed that adversarial attacks alter the decision basis of the model.This is reflected in the misalignment of the model’s attention regions, thereby aiding in the exploration of the operation mechanism of adversarial attacks.…”
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Improved Algorithm for Vehicle Bottom Safety Detection Based on YOLOv8n: PSP-YOLO by Di Zhao, Yulin Cheng, Sizhe Mao

“…The safety inspection system for the underside of vehicles demands both high detection speed and accuracy, necessitating a model with small parameters and high network efficiency. To address these issues and improve the real-time performance of under-vehicle safety inspection, the YOLOv8n object-detection algorithm was enhanced, resulting in the PSP-YOLO algorithm. …”
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Research on UAV aerial imagery detection algorithm for Mining-Induced surface cracks based on improved YOLOv10 by Jiayong An, Siyuan Dong, Xuanli Wang, Chenlei Li, Wenpei Zhao

“…Secondly, the Small Object Feature Enhancement Pyramid (SOFEP) enhances detail representation of small cracks in complex backgrounds.Furthermore, we propose a weighted combination strategy of Normalized Wasserstein Distance (NWD) and IoU loss, balancing sensitivity to zero-overlap instances and robustness against scale deviations, thereby improving localization accuracy and generalization capability. …”
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Research on Multi-Target Detection and Tracking of Intelligent Vehicles in Complex Traffic Environments Based on Deep Learning Theory by Xuewen Chen, Shilong Yan, Chenxi Xia

“…To address the issues of missed detections and false detections of small target missed detections caused by dense occlusion in complex traffic environments, a non-maximum suppression method, Bot-NMS, is proposed to achieve accurate prediction and localization of occluded targets. …”
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Ultra-Short Baseline Synthetic Aperture Passive Positioning Based on Interferometer Assistance by Gaogao Liu, Qidong Zhang, Jian Xu, Jiangbo Zhu, Ziyu Huang, Beibei Mu, Hongfu Guo

“…In addition, the Cramer–Rao lower bound (CRLB) of the localization for this method is derived. The simulation and unmanned aerial vehicle (UAV) experimental results demonstrate the effectiveness and feasibility of this method.…”
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Knowledge distillation-enhanced marine optical remote sensing object detection with transformer and dual-path architecture by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Jinlin Chen

“…The encoder integrates a Holistic Focal Feature Interwined (HFFI) module that employs parallel pathways to progressively refine local textures and global semantic representations, enabling adaptive feature fusion across spatial hierarchies. …”
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GESC-YOLO: Improved Lightweight Printed Circuit Board Defect Detection Based Algorithm by Xiangqiang Kong, Guangmin Liu, Yanchen Gao

“…Currently, existing PCB defect detection models are beset with issues such as excessive model size and parameter complexity, rendering them ill-equipped to meet the requirements for lightweight deployment on mobile devices. …”
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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…Secondly, to mitigate the issue of low pixel utilization ratio in small-target detection, a DTADH module is designed, and a shared feature interaction module is constructed. …”
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A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks by B Nagarajan, Santhosh Kumar SVN, M Selvi, K Thangaramya

“…Moreover, the F-CSO provides improved localization to locate the defective sensor nodes that are present in the WSN. …”
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Shoeprints on Shoe covers Obtained Using Special Thermal Devices as Objects of Traceological Forensic Examination by I. V. Latyshov

“…The article deals with the issues of traceological forensic examination of shoeprints generated while putting shoe covers upon shoes using special thermal devices, and during subsequent walking in shoes. …”
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Impact of Critical Situations on Autonomous Vehicles and Strategies for Improvement by Shahriar Austin Beigi, Byungkyu Brian Park

“…GPS and sensor signals can be disturbed in urban canyons and forested regions, which pose vehicle localization and navigation problems. Both roadway infrastructure issues, like inadequate signage and poor road conditions, are major challenges to AV sensors and navigation systems. …”
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AJANet: SAR Ship Detection Network Based on Adaptive Channel Attention and Large Separable Kernel Adaptation by Yishuang Chen, Jie Chen, Long Sun, Bocai Wu, Hui Xu

“…This method effectively reduces false positives, missed detections, and localization ambiguities, especially in complex inshore environments. …”
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DIGITAL DIPLOMACY AS A MEANS OF STRATEGIC STATE COMMUNICATION by Valery Kononenko, Tetiana Komarova

“…The article is devoted to the specific issues of challenges to political decision-making processes in the field of digital diplomacy: virtualization of social and political processes, the state of uncertainty, instability, fluidity in the global space, latency, uncoordinated influence of centers of power (power), the circle of which has significantly expanded, the struggle for informational dominance, for reducing the information space and opportunities of opponents. …”
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UniText: A Unified Framework for Chinese Text Detection, Recognition, and Restoration in Ancient Document and Inscription Images by Lu Shen, Zewei Wu, Xiaoyuan Huang, Boliang Zhang, Su-Kit Tang, Jorge Henriques, Silvia Mirri

“…The model adopts a multi-task architecture that integrates spatial localization, semantic recognition, and visual restoration through stroke-aware supervision and multi-scale feature aggregation. …”
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Glocalization Self-Referential Remembrances by Roland Robertson

“…In tracing this history, I shall obviously speak about the changes in, and fortunes of, the better-known concept of globalization as well as the “lesser” concept of localization. Being a sociologist – more appropriately now, a transdisciplinarian – I shall also focus upon the increasingly significant branch of social/natural science that addresses such issues as climate change, biodiversity and the debate about the Anthropocene. …”
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Multilayer Concept Drift Detection Method Based on Model Explainability by Haolan Zhang, Xinyi Chen, Min Hu, Vijayan Sugumaran

“…However, existing concept drift detection methods face challenges in achieving a proper balance between accuracy and timeliness while also disregarding the precise localization of the drift point. To address these issues, this paper presents a novel three-layer drift detection algorithm named Hierarchical Concept Drift Detection based on SHapley Additive exPlanations (HCDD-SHAP). …”
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A unified approach for weakly supervised crack detection via affine transformation and pseudo label refinement by Zhongmin Huangfu, Yibo Jiao, Fupeng Wei, Ge Shi, Hangcheng Dong

“…Current deep neural network visual interpretation approaches have issues including erroneous target localization. This study proposes an Affine Transformation and Pseudo Label Refinement (AT-CAM) method. …”
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Modélisation géomatique par évaluation multicritère pour la prospection des sites d’agriculture urbaine à Ouagadougou by Conchita M. G. Kêdowidé

“…Agriculture in urban areas is a solution to problems such as food security, unemployment, environment issues, green spaces creation and so on. In spite of its major importance in developing countries, agriculture in urban areas is victim to a lack of recognition and to an important economical weight leading this business line to precariousness and informal. …”
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DelAwareCol: Delay Aware Collaborative Perception by Ahmed N. Ahmed, Siegfried Mercelis, Ali Anwar

“…Firstly, an intra-agent information aggregation module captures valuable semantic cues within the temporal context to enhance the local representation of each ego agent. Secondly, an inter-agent information aggregation module manages inter-agent interactions and spatial relationships, addressing common vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) issues, such as spatial misalignment, asynchronous information sharing, and pose errors. …”
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A three-stage exercise-oriented problem-based learning model for double-weak students in applied undergraduate education by Xianbin Huang, Xianbin Huang, Yao Hu, Liming Chen

“…Empirical research reveals that the traditional Project-Based Learning (PBL) model exhibits adaptability issues, such as insufficient foundational skill support and low knowledge transfer efficiency. …”
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