The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…A rice impurity detection algorithm model, DE-YOLO, based on YOLOX-s improvement is proposed to address the issues of small crop target recognition and the similarity of impurities in rice impurity detection. …”
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Research on underwater disease target detection method of inland waterway based on deep learning by Tao Yu, Yu Xie, Jinsong Luo, Wei Zhu, Jie Liu

“…Abstract Aiming at the problems of low detection accuracy and poor generalization ability of underwater disease targets in inland waterways, an underwater disease target detection algorithm for inland waterways based on improved YOLOv5 is designed, which is denoted as YOLOv5-GBCE. …”
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Combined Thermal Index Development for Urban Heat Island Detection in Area of Split, Croatia by Majda Ćesić, Katarina Rogulj, Andrija Krtalić

“…UHIs are becoming an increasingly common problem in large cities, which appear due to excessive urbanization and reductions in natural cover and vegetation. …”
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Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology by C. Jayasri, V. Balaji, C. M. Nalayini, S. Pradeep

“…To address this problem, this study proposes an enhanced deep learning-based optimization framework for detecting cyberattacks in vehicle networks. …”
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MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…Multi-label attribute recognition is a critical task in computer vision, with applications ranging across diverse fields. This problem often involves detecting objects with multiple attributes, necessitating sophisticated models capable of both high-level differentiation and fine-grained feature extraction. …”
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LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…In the feature fusion part, aiming to improve the detection performance for small objects in UAV aerial images, a shallow feature fusion network and a small object detection head are added. …”
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A Parts Detection Network for Switch Machine Parts in Complex Rail Transit Scenarios by Jiu Yong, Jianwu Dang, Wenxuan Deng

“…The rail transit switch machine ensures the safe turning and operation of trains on the track by switching switch positions, locking switch rails, and reflecting switch status in real time. However, in the detection of complex rail transit switch machine parts such as augmented reality and automatic inspection, existing algorithms have problems such as insufficient feature extraction, large computational complexity, and high demand for hardware resources. …”
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Application research of sample data generation based on improved Cycle-GAN in intrusion detection by ZENG Qingpeng, GUO Hangkai

“…This indicates that the proposed method effectively addressed the problems of slow data updates and insufficient samples for certain intrusion categories in intrusion detection.…”
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Remote Sensing Change Detection With Forward–Backward Diffusion and Multidirectional Scanning by Hexin Yuan, Peng Wang, Haibo Wang, Cui Ni, Yali Liu, Chao Ma

“…In addition, a significant issue remains in the detection of large continuous change regions, which often leads to leakage problems. …”
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Cloud-Edge Collaborative Defect Detection Based on Efficient Yolo Networks and Incremental Learning by Zhenwu Lei, Yue Zhang, Jing Wang, Meng Zhou

“…This paper addresses the problem of insufficient detection accuracy of existing lightweight models on resource-constrained edge devices by presenting a new lightweight YoloV5 model, which integrates four modules, SCDown, GhostConv, RepNCSPELAN4, and ScalSeq. …”
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DAKBNet: Multiscale Fusion With Dynamic Assembly Kernels and Bilateral Feature Enhancement for Land Use Classification of Remote Sensing Images by Chenke Yue, Yin Zhang, Junhua Yan, Zhaolong Luo, Yong Liu, Pengyu Guo

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Electricity Theft Detection Using Rule-Based Machine Leaning (rML) Approach by Sheyda Bahrami, Erol Yumuk, Alper Kerem, Beytullah Topçu, Ahmetcan Kaya

“…Power companies can use the information gathered by Advanced Metering Infrastructure (AMI) to create data-driven, machine learning-based approaches for Electricity Theft Detection (ETD) in order to solve this problem. The majority of data-driven methods for detecting power theft do take usage trends into account while doing their analyses. …”
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Pest detection in dynamic environments: an adaptive continual test-time domain adaptation strategy by Rui Fu, Shiyu Wang, Mingqiu Dong, Hao Sun, Mohammed Abdulhakim Al-Absi, Kaijie Zhang, Qian Chen, Liqun Xiao, Xuewei Wang, Ye Li

“…The MT-DAM integrates an object detection model with an image segmentation model, exchanging information through feature fusion at the feature extraction layer. …”
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Intelligent UAV health monitoring: Detecting propeller and structural faults with MEMS-based vibration by Temel Sonmezocak

“…The model achieved a maximum accuracy of 99.40 % in detecting the severity of propeller damage. Furthermore, the study also investigated loosening conditions in the propeller rotor and UAV carrier arm screws, demonstrating that, in combination with propeller faults, other mechanical loosening problems can be detected with a maximum accuracy of 95.86 %, highlighting the superior performance of the proposed approach.…”
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Connected Vehicles Security: A Lightweight Machine Learning Model to Detect VANET Attacks by Muawia A. Elsadig, Abdelrahman Altigani, Yasir Mohamed, Abdul Hakim Mohamed, Akbar Kannan, Mohamed Bashir, Mousab A. E. Adiel

“…In other words, two layers of enhancements were applied—using a suitable feature selection technique and fixing the dataset imbalance problem. …”
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Unmanned Aerial Vehicle Anomaly Detection Based on Causality-Enhanced Graph Neural Networks by Chen Feng, Jun Fan, Zhiliang Liu, Guang Jin, Siya Chen

“…With the widespread application of unmanned aerial vehicles (UAVs), the safety detection system of UAVs has created an urgent need for anomaly detection technology. …”
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SAR Images Change Detection Based on Attention Mechanism-Convolutional Wavelet Neural Network by Jiahui E, Lu Wang, Chunhui Zhao, P. Takis Mathiopoulos, Tomoaki Ohtsuki, Fumiyuki Adachi

“…To deal with these problems this article proposes a SAR images change detection scheme which is based upon an Attention Mechanism and Convolutional Wavelet Neural Network. …”
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Detection of Masses in Mammogram Images Based on the Enhanced RetinaNet Network With INbreast Dataset by Wang M, Liu R, Luttrell IV J, Zhang C, Xie J

“…Therefore, we adopted and enhanced RetinaNet to detect masses in mammogram images. Specifically, we introduced a novel modification to the network structure, where the feature map M5 is processed by the ReLU function prior to the original convolution kernel. …”
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A Precise Detection Method for Tomato Fruit Ripeness and Picking Points in Complex Environments by Xinfa Wang, Xuan Wen, Yi Li, Chenfan Du, Duokuo Zhang, Chengxiu Sun, Bihua Chen

“…Aiming at the problems faced in practical applications, such as low accuracy of tomato ripeness and picking points detection in complex greenhouse environments, which leads to wrong picking, missed picking, and fruit damage by robots, this study proposes the YOLO-TMPPD (Tomato Maturity and Picking Point Detection) model. …”
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Context guided transformer enhanced YOLOv8 for accurate juvenile abalone detection and counting by Dapeng Cheng, Ji Ruan, Xinhao Li, Feng Zhao, Shoudu Zhang, Guofan Zhang, Fucun Wu

“…In this study, we introduce the Context Guided Transformer YOLO (CGT-YOLO) model to tackle the problem, utilizing You Only Look Once version 8 (YOLOv8) as the foundational model for detecting and counting juvenile abalones. …”
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