Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

“…The spread of fake news through on-line platforms poses a significant threat to public trust and social stability, especially in resource-constrained Chinese domains. Existing Fake News Detection (FND) models often lack transparency, functioning as “black boxes” that limit their practical utility. …”
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TEDVIL: Leveraging Transformer-Based Embeddings for Vulnerability Detection in Lifted Code by Gary A. McCully, John D. Hastings, Shengjie Xu

“…Notably, these results are achieved when the embedding model is trained with a dataset of just 48,000 functions, demonstrating effectiveness in resource-constrained settings. …”
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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques.…”
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Plug-and-Play Robust Aerial Object Detection Under Hazy Conditions by Wei Wu, Hao Chang, Zhiwen Chen, Zhu Li

“…Moreover, we also propose a detection feature pyramid loss function to more accurately restore object features. …”
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DEM-based topographic change detection considering the spatial distribution of errors by Yufeng He, Shaohua Lei, Wen Dai, Xi Chen, Bo Wang, Yehua Sheng, Hui Lin

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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

“…However, traditional methods of tire defect detection have encountered problems such as slow detection speed, complex tire defect backgrounds, and limited hardware resources. …”
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Lightweight obstacle detection for unmanned mining trucks in open-pit mines by Guangwei Liu, Jian Lei, Zhiqing Guo, Senlin Chai, Chonghui Ren

“…In addition, this paper also adopts the amplitude-based layer adaptive sparse pruning algorithm (LAMP) to further compress the model size while maintaining efficient detection performance. Through this pruning strategy, the model further reduces its dependence on computing resources while maintaining key performance. …”
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Identification, functional analysis, and clinical applications of defective viral genomes by Xiaowei Yan, Yitong Pan, Peiying Li, Li Zhu, Jianhai Yu, Chenguang Shen, Bao Zhang, Wei Zhao

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Optimization of train obstacle detection based on zone media controller unit by ZHOU Liming, HU Jiaqiao, SHEN Tuo

“…In addition, the need for comprehensive train detection including pantograph-catenary systems and running gears, lead to an increased number of on-board devices, resulting in fewer computational resources available for each detection system, and complicating equipment installation and maintenance. …”
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A review of deep learning models to detect malware in Android applications by Elliot Mbunge, Benhildah Muchemwa, John Batani, Nobuhle Mbuyisa

“…Smartphone applications use permissions to allow users to utilize different functionalities, making them susceptible to malicious software (malware). …”
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Myoglobin expression improves T-cell metabolism and antitumor effector function by Haifeng C Xu, Diran Herebian, Ertan Mayatepek, Dirk Brenner, Aleksandra A Pandyra, Philipp A Lang, Sascha Dietrich, Julia Werner, Georgios Theodorakis, Ichiro Katahira, Mitrajit Ghosh, Michal Gorzkiewicz, Luisa de Sousa Santos, Ann Kathrin Bergmann, Max Anstötz, Anne Busch, Carsten Berndt

“…Although T cells expressing Mb exhibited increased expression of effector cytokines, PD-1 was still detected and targetable by anti-PD-1 monoclonal antibodies, which in combination with transfer of Mb-expressing T cells demonstrated maximal efficacy in delaying tumor growth.Conclusion Taken together, we show that expression of Mb in T cells can increase their metabolism, infiltration into the tumor tissue, and effector function against cancer cells.…”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

“…High-precision underwater object detection is a crucial component for improving the efficiency of marine resource development. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…The model and method for ensuring the robustness of resource-constrained neural network systems for object detection in aerial video surveillance. …”
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3L-YOLO: A Lightweight Low-Light Object Detection Algorithm by Zhenqi Han, Zhen Yue, Lizhuang Liu

“…Existing methods often use image enhancement to improve detection, which results in a large amount of computational resource consumption. …”
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Automatic detection of foreign object intrusion along railway tracks based on MACENet. by Xichun Chen, Yu Tian, Ming Li, Bin Lv, Shuo Zhang, Zixian Qu, Jianqing Wu, Shiya Cheng

“…Ensuring high accuracy and efficiency in foreign object intrusion detection along railway lines is critical for guaranteeing railway operational safety under limited resource conditions. …”
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Rice disease detection method based on multi-scale dynamic feature fusion by Qian Fan, Runhao Chen, Bin Li

“…These optimizations enable efficient deployment on resource-constrained mobile devices, making the model highly suitable for real-time disease detection in practical agricultural scenarios where hardware limitations are critical. …”
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Real time wire rope detection method based on Rockchip RK3588 by Mengpeng Qian, Yong Wang, Shaoqing Liu, Zhanghou Xu, Zhenshan Ji, Ming Chen, Hailong Wu, Zuchao Zhang

“…To enhance non-destructive wire rope inspection, a Mini-YOLO model was developed by integrating MobileNetV3, the Coordinate Attention (CA) mechanism, and a novel loss function, Inner-IoU, into the YOLOv8 framework. This paper’s innovation lies not in creating algorithmic components from scratch, but in their synergistic integration and targeted optimization to solve the specific challenges of real-time defect detection on resource-constrained edge devices. …”
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An improved lightweight tiny-person detection network based on YOLOv8: IYFVMNet by Fan Yang, Lihu Pan, Hongyan Cui, Linliang Zhang

“…IntroductionIn the aviation field, drone search and rescue is a highly urgent task involving small target detection. In such a resource-constrained scenario, there are challenges of low accuracy and high computational requirements.MethodsThis paper proposes IYFVMNet, an improved lightweight detection network based on YOLOv8. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…Finally, the Inner-IoU optimization loss function is applied to accelerate model convergence and enhance detection accuracy.ResultsTesting results indicate that SGSNet performs exceptionally well across key metrics, achieving 98.83% precision, 99.45% recall, 99.14% F1 score, 99.50% mAP@0.5, and a loss value of 0.3534. …”
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