Detection of Maize Pathogenic Fungal Spores Based on Deep Learning by Yijie Ren, Ying Xu, Huilin Tian, Qian Zhang, Mingxiu Yang, Rongsheng Zhu, Dawei Xin, Qingshan Chen, Qiaorong Wei, Shuang Song

“…Traditional spore detection methods struggle to identify spore-level targets within complex backgrounds. …”
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Advances in Object Detection and Localization Techniques for Fruit Harvesting Robots by Xiaojie Shi, Shaowei Wang, Bo Zhang, Xinbing Ding, Peng Qi, Huixing Qu, Ning Li, Jie Wu, Huawei Yang

“…The accuracy of object detection and location is directly related to the picking efficiency, quality and speed of fruit-harvesting robots. …”
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A Comparative Study on Detection and Recognition of Nonuniform License Plates by Mehak Arshid, Muhammad Raees Azam, Zahid Mahmood

“…In addition, a detailed computational complexity comparison on various image resolutions revealed that E2E and the CA-CenterNet are more efficient than their counterparts during detection and recognition tasks, respectively.…”
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Attribute grouping-based categorical outlier detection using causal coupling weight by Yijing Song, Jianying Liu, Jifu Zhang

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Enhanced U-Net++ for Improved Semantic Segmentation in Landslide Detection by Meng Tang, Yuelin He, Muhammed Aslam, Edore Akpokodje, Syeda Fizzah Jilani

“…Landslide detection and segmentation are critical for disaster risk assessment and management. …”
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CNN and Transfer Learning methods for enhanced dermatological disease detection by Habibulla C. Venkataiah, T. Jayachandra Prasad, G. Gopinath, B. Charitha, G. Dharma Teja, B. Lomith Reddy

“…This final model has been a pragmatic and accessible tool for early detection and diagnosis of skin disease. The feature here is an attempt to provide a more accurate, efficient, and user-friendly diagnostic solution through the incorporation of advanced methods of Transfer Learnin3g and visualization.…”
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A Comprehensive Investigation of Fraud Detection Behavior in Federated Learning by Sun Rui

“…While ANN and CNN demonstrate strong capacity in identifying complex fraud patterns, their communication efficiency and overfitting challenges are significant. …”
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An annotated Dataset and Benchmark for Detecting Floating Debris in Inland Waters by Guangchao Qiao, Mingxiang Yang, Hao Wang

“…However, complex light conditions in the water, small size objects and other factors pose a huge challenge for floating object detection. …”
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Coral reef detection using ICESat-2 and machine learning by Gabrielle A. Trudeau, Kim Lowell, Jennifer A. Dijkstra

“…These obstacles were mitigated through the integration of algorithmically derived pseudo-rugosity and slope metrics as innovative proxies for seafloor complexity, significantly improving predictive performance. …”
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Image Target Detection and Recognition Method Using Deep Learning by Hongyan Sun

“…Finally, the experimental results showed that the image target detection and recognition algorithm proposed in this paper can be better applied to image target detection and classification in complex environment and had higher detection efficiency and recognition accuracy than the existing models. …”
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Improved RRT-Based Obstacle-Avoidance Path Planning for Dual-Arm Robots in Complex Environments by Jing Wang, Genliang Xiong, Bowen Dang, Jianli Chen, Jixian Zhang, Hui Xie

“…To address the obstacle-avoidance path-planning requirements of dual-arm robots operating in complex environments, such as chemical laboratories and biomedical workstations, this paper proposes ODSN-RRT (optimization-direction-step-node RRT), an efficient planner based on rapidly-exploring random trees (RRT). …”
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Leveraging Deep Learning for Fault Detection and Localization in Distributed Systems by Debolina Ghosh, Jay Prakash Singh

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Algorithm Improvement for Mobile Event Detection with Intelligent Tunnel Robots by Li Wan, Zhenjiang Li, Changan Zhang, Guangyong Chen, Panming Zhao, Kewei Wu

“…Mobile inspections conducted by intelligent tunnel robots are instrumental in broadening the inspection reach, economizing on inspection expenditures, and augmenting the operational efficiency of inspections. Despite differences from fixed surveillance, mobile-captured traffic videos have complex backgrounds and device conditions that interfere with accurate traffic event identification, warranting more research. …”
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HCRP-YOLO: A lightweight algorithm for potato defect detection by Haojie Liao, Guanping Wang, Siyu Jin, Yan Liu, Wei Sun, Sen Yang, Lu Wang

“…In response, this study proposes HCRP-YOLO system, which is based on the YOLOv8n architecture and aims to further enhance lightweight, precision, and efficiency. The method first introduces the lightweight HGNetv2 backbone network and incorporates a channel scaling feature to reduce model complexity, while dynamically adjusting the number of feature channels, thereby improving detection performance. …”
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Inner Ear Multiple Primary Cell Type Detection System by Yu-Ting Li, Ching-Yun Chen, Bing-Siang Wang, Po-Hsuan Hung, Chia-Yu Lin

“…Overall, IEP-CDS effectively improves the efficiency of IEP detection in developing cell therapy for inner ear organoids.…”
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Lightweight detection algorithms for small targets on unmanned mining trucks by Shuoqi CHENG, Yilihamu·YAERMAIMAITI, Lirong XIE, Xiyu LI, Ying MA

“…It enhances multi-scale feature fusion capability via weighted feature fusion, significantly reducing parameter count while improving small target detection capability. Additionally, it designs a detection decoupling head with a multi-head attention mechanism to improve the issue of network complexity caused by convolutional layer redundancy, processes spatial dimensions to focus on capturing target features, reduces interference from irrelevant backgrounds, and enhances the accuracy of occluded target recognition.urthermore, it constructs a lightweight neural network with dual convolution (CDC), enhancing inter-channel information flow, improving model feature expression capability, and reducing model complexity. …”
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Machine Learning Detection of Melting Layers From Radar Observations by Yan Xie, Fraser King, Claire Pettersen, Mark Flanner

“…Compared to a traditional detection method, the U‐Net model increases the Probability of Detection by 57% and improves the mean Dice‐Sørensen coefficient from 0.69 to 0.91. …”
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Evaluating Lightweight Transformers With Local Explainability for Android Malware Detection by Fatima Bourebaa, Mohamed Benmohammed

“…Traditional deep learning-based Android malware detection, reliant on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), struggles to capture long-range dependencies, which are critical for identifying complex malware patterns. …”
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An intelligent algorithm to fast and accurately detect chaotic correlation dimension by Mengyan Shen, Miaomiao Ma, Zhicheng Su, Xuejun Zhang

“…Abstract Detecting the complexity of natural systems, such as hydrological systems, can help improve our understanding of complex interactions and feedback between variables in these systems. …”
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Circle Detection with Adaptive Parameterization: A Bottom-Up Approach by Lin Han, Yan Zhuang, Ke Chen, Yuhua Xie, Guoliang Liao, Guangfu Yin, Jiangli Lin

“…Circle detection remains a critical yet challenging task in computer vision, particularly under complex imaging conditions where existing measurement methods face persistent challenges in parameter configuration and noise resilience. …”
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