Improved Algorithm to Detect Clandestine Airstrips in Amazon RainForest by Gabriel R. Pardini, Paulo M. Tasinaffo, Elcio H. Shiguemori, Tahisa N. Kuck, Marcos R. O. A. Maximo, William R. Gyotoku

“…By addressing the limitations identified in the initial approach, this refined algorithm aims to improve detection accuracy and operational efficiency in complex rainforest environments. …”
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Green Apple Detector Based on Optimized Deformable Detection Transformer by Qiaolian Liu, Hu Meng, Ruina Zhao, Xiaohui Ma, Ting Zhang, Weikuan Jia

“…However, due to the complex orchard environment, the ever-changing posture of the target fruit, and the difficulty of detecting green target fruit similar to the background, they bring new challenges to the detection of green target fruit. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…This study pioneers an innovative framework, using Multi-Scale Discriminative Robust Local Binary Pattern (MS-DRLBP) features, combined with a hybrid Convolutional Neural Network-Radial Basis Function (CNN-RBF) classifier, to enhance the detection of DR. Inspired by principles of randomization-based learning, our approach incorporates elements of stochastic modeling within the CNN-RBF architecture to optimize feature extraction and classification, mirroring the efficiency of non-iterative training processes. …”
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Research on Surface Defect Detection of Rare-Earth Magnetic Materials Based on Improved SSD by Bin Zhang, Shuqi Fang, Zhixi Li

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Lightweight highland barley detection based on improved YOLOv5 by Minghui Cai, Hui Deng, Jianwei Cai, Weipeng Guo, Zhipeng Hu, Dongzheng Yu, Houxi Zhang

“…In addition,the proposed model outperformed mainstream object detection algorithms such as Faster R-CNN, Mask R-CNN, RetinaNet, YOLOv7, and YOLOv8, in terms of detection accuracy and computational efficiency. …”
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Design and Implementation of an Assistive Real-Time Red Lionfish Detection System for AUV/ROVs by M-Mahdi Naddaf-Sh, Harley Myler, Hassan Zargarzadeh

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DCFE-YOLO: A novel fabric defect detection method. by Lei Zhou, Bingya Ma, Yanyan Dong, Zhewen Yin, Fan Lu

“…However, the task of fabric defect detection remains highly challenging due to the complex textures and diverse defect patterns. …”
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Implementation of YOLOv7 Model for Human Detection in Difficult Conditions by Arijal B, Andi Sunyoto, M. Hanafi

“…The rapid development of artificial intelligence technology in recent decades has led to the development of highly efficient object detection algorithms, including human detection under difficult conditions. …”
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Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…In intelligent building, efficient surface defect detection is crucial for structural safety and maintenance quality. …”
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YOLOv11-HRS: An Improved Model for Strawberry Ripeness Detection by Jianhua Liu, Jing Guo, Suxin Zhang

“…Automated ripeness detection in large-scale strawberry cultivation is often challenged by complex backgrounds, significant target scale variation, and small object size. …”
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Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…Abstract Semantic Change Detection (SCD) aims to accurately identify the change areas and their categories in dual-time images, which is more complex and challenging than traditional binary change detection tasks. …”
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Method for Detecting Tiny Defects on Machined Surfaces of Mechanical Parts Based on Object Recognition by Haotian Li, Zhen Wang, Lipeng Qiu, Xichu Wei

“…Practical results demonstrate that this method outperforms traditional approaches in terms of missed detection rates and detection efficiency, effectively addressing the challenge of detecting complex machining surface defects, and providing a high-precision, high-efficiency defect detection solution for the mechanical part machining field.…”
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SARE: an optimized method for detection functional regulatory elements in genome by Mohammadjavad Hosseinpoor

“…This is primarily due to the complexity of health data, particularly genomic and epigenetic datasets. …”
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AI in dermatology: a comprehensive review into skin cancer detection by Kavita Behara, Ernest Bhero, John Terhile Agee

“…Background Artificial Intelligence (AI) is significantly transforming dermatology, particularly in early skin cancer detection and diagnosis. This technological advancement addresses a crucial public health issue by enhancing diagnostic accuracy, efficiency, and accessibility. …”
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Contrastive learning of cross-modal information enhancement for multimodal fake news detection by Weijie Chen, Fei Cai, Yupu Guo, Zhiqiang Pan, Wanyu Chen, Yijia Zhang

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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

“…First, we introduce an efficient multiscale convolutional (EMSC) module to improve feature extraction from complex backgrounds and enhance multiscale representation. …”
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MODEL BASED FAULT DETECTION FOR SAFETY MANAGEMENT OF THE INDUSTRIAL PROCESSES by Dumitru POPESCU, Pierre BORNE, Crina TOROUS

“…Detection and diagnosis are important actions offered by the complex automations, that contribute to keeping the exploitation of the process safe. …”
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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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Crack Detection on Road Surfaces Based on Improved YOLOv8 by Haiyang Wu, Lingyun Kong, Denghui Liu

“…Road defect detection is vital for road maintenance but remains challenging due to the complexity of backgrounds, low resolution, and crack similarity. …”
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Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data by Nicholas Fiorentini, Massimo Losa

“…However, the management, monitoring, and maintenance of road networks remain a challenge, particularly given limited budgets and the complexity of assessing widespread infrastructure. This Special Issue on “Road Detection, Monitoring, and Maintenance Using Remotely Sensed Data” presents innovative strategies leveraging remote sensing technologies, artificial intelligence (AI), and non-destructive testing (NDT) to optimize road infrastructure assessment. …”
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