ZFD-Net: Zinc flower defect detection model of galvanized steel surface based on improved YOLOV5. by Yang Gao, Hanquan Zhang, Lifu Zhu, Feitong Xie, Dong Xiao

“…Then we propose a cross resnet simam fasternet (CRSFN) module to improve the reasoning speed of ZFD-Net and ensure the detection effect of zinc flower defects. Finally, we construct a high-quality dataset of zinc flower defect (ZFD) detection on galvanized sheet surface, which solves the problem that no public dataset is available at present. …”
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A New Scheduling Quantitative Feedback Theory-Based Controller Integrated with Fault Detection for Effective Vibration Control by R. Jeyasenthil, Yang-Sup Lee, Seung-Bok Choi

“…In this work, a new integrated fault detection and control (IFDC) method is presented for single-input/single-output systems (SISOs). …”
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Wheel Tread Dynamic Detection Benchmark Positioning Method Based on Iterative Reweighted Least-squares Line Fitting by LI Miaocheng, WANG Junping, SHEN Yunbo, YOU Yong, DAI Bowang, LAN Qiangqiang

“…Reference positioning of inner side benchmark is a traditional method for tread detection but there are problems of positioning error caused by field factors in wheel tread dynamic detection such as reference tilt by hunting, foreign matter and light interference. …”
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A Hybrid Deep Learning Approach for Cotton Plant Disease Detection Using BERT-ResNet-PSO by Chetanpal Singh, Santoso Wibowo, Srimannarayana Grandhi

“…This study shows that the hybrid deep learning approach is capable of dealing with the cotton plant disease detection problem effectively. This study suggests that the proposed approach is beneficial to help avoid crop losses on a large scale and support effective farming management practices.…”
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DeFRCN-MAM: DeFRCN and multi-scale attention mechanism-based industrial defect detection method by Tong Zheng, Liangbing Sa, Chongchong Yu, Aibin Song

“…Different from general visual objects, industrial defects have the characteristics of small sample, weak visibility and irregular shape, which hinder the application of related studies. According to these problems, a few-shot object detection (FSOD) method based on Decoupled Faster R-CNN (DeFRCN) is proposed in this paper. …”
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DETECTION OF NON-MELANOMA SKIN CANCER BY DEEP CONVOLUTIONAL NEURAL NETWORK AND STOCHASTIC GRADIENT DESCENT OPTIMIZATION ALGORITHM by Premananda Sahu, Srikanta Kumar Mohapatra, Prakash Kumar Sarang, Jayashree Mohanty, Pradeepta Kumar Sarangi

“…The expansion of skin problems for human beings has emerged as a significant problem, and the successful investigation has been observed as an arduous task for clinical experts or dermatologists. …”
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PCB Electronic Component Soldering Defect Detection Using YOLO11 Improved by Retention Block and Neck Structure by Youzhi Xu, Hao Wu, Yulong Liu, Xing Zhang

“…The single-stage target detection algorithm has a faster running time, but the detection accuracy needs to be improved. …”
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QuantumNet: An enhanced diabetic retinopathy detection model using classical deep learning-quantum transfer learning by Manish Bali, Ved Prakash Mishra, Anuradha Yenkikar, Diptee Chikmurge

“…The method is as follows: • Evaluate three classical deep learning models—CNN, ResNet50, and MobileNetV2—using the APTOS 2019 blindness detection dataset on Kaggle to identify the best-performing model for integration. • QuantumNet combines the best-performing classical DL model for feature extraction with a variational quantum classifier, leveraging quantum transfer learning for enhanced diagnostics, validated statistically and on Google Cirq using standard metrics. • QuantumNet achieves 94.11 % accuracy, surpassing classical DL models and prior research by 11.93 percentage points, demonstrating its potential for accurate, efficient DR detection and broader medical imaging applications.…”
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Accurate Detection and Tracking of Small-Scale Vehicles in High-Altitude Unmanned Aerial Vehicle Bird-View Imagery by Heshan Zhang, Xin Tan, Mengwei Fan, Cunshu Pan, Zhanji Zheng, Shuang Luo, Jin Xu

“…Experiments show that the proposed method can significantly improve the detection accuracy of the network and effectively solve the problems of missed detection and false positives in small-scale vehicle tracking tasks in high-resolution aerial images captured by high-altitude UAVs. …”
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Advanced retinal disease detection from OCT images using a hybrid squeeze and excitation enhanced model. by Gülcan Gencer, Kerem Gencer

“…The combination of these architectures enhances both the efficiency and classification performance of the model, enabling more accurate detection of retinal disorders from OCT images. Additionally, SE blocks increase the representational ability of the network by adaptively recalibrating per-channel feature responses.…”
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Federated Deep Learning for Scalable and Privacy-Preserving Distributed Denial-of-Service Attack Detection in Internet of Things Networks by Abdulrahman A. Alshdadi, Abdulwahab Ali Almazroi, Nasir Ayub, Miltiadis D. Lytras, Eesa Alsolami, Faisal S. Alsubaei, Riad Alharbey

“…We need scalable, privacy-preserving, and resource-efficient IoT intrusion detection algorithms to solve this essential problem. …”
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Novel fusion of color balancing and superpixel based approach for detection of tomato plant diseases in natural complex environment by Saiqa Khan, Meera Narvekar

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Employing CNN mobileNetV2 and ensemble models in classifying drones forest fire detection images by Dima Suleiman, Ruba Obiedat, Rizik Al-Sayyed, Shadi Saleh, Wolfram Hardt, Yazan Al-Zain

“…As documented in the literature, MobileNetV2 consistently outperforms other architectures in computational efficiency and provides an excellent balance between efficiency and the quality of learned features over multiple epochs. This study underscores the suitability of MobileNetV2 for real-time applications on drones, particularly for the detection of forest fires in resource-constrained environments. …”
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LightYOLO: Lightweight model based on YOLOv8n for defect detection of ultrasonically welded wire terminations by Jianshu Xu, Lun Zhao, Yu Ren, Zhigang Li, Zeshan Abbas, Lan Zhang, Md Shafiqul Islam

“…Therefore, to solve the above problems, we propose a fast and effective lightweight detection model based on You Only Look Once v8 (YOLOv8n), named LightYOLO. …”
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View on the problem of diabetic nephropathy in children and adolescents with type 1 diabetes mellitus: the role of renin-angiotensin-aldosterone system (literature review) (part 1) by K. V. Skobeleva, L. V. Tyrtova, I. L. Nikitina, A. S. Olenev

“…Renin-angiotensin-aldosterone system makes a significant contribution to its development. These features require the creation of new diagnostic techniques for earlier detection of the pathology.…”
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Enhancing FTIR Spectral Feature Construction for Aero-Engine Hot Jet Remote Sensing via Integrated Peak Refinement and Higher-Order Statistical Fusion by Zhenping Kang, Yurong Liao, Xinyan Yang, Zhaoming Li

“…It adopted an adaptive threshold for the initial coarse detection of peaks, enhanced the positioning accuracy through local gradient optimization, dynamically screened the local strongest peak according to intensity information, and resolved the problem of overlapping peak resolution via an intelligent merging strategy based on the physical characteristics of spectral lines, achieving high-precision and high-robustness peak feature extraction. …”
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An intelligent optimized object detection system for disabled people using advanced deep learning models with optimization algorithm by Marwa Obayya, Fahd N. Al-Wesabi, Menwa Alshammeri, Huda G. Iskandar

“…Visually impaired persons (VIPs) can utilize the OD approach for detecting problems and recognizing services to offer secure and informative navigation. …”
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TWO-PARAMETER IRT MODEL APPLICATION TO ASSESS PROBABILISTIC CHARACTERISTICS OF PROHIBITED ITEMS DETECTION BY AVIATION SECURITY SCREENERS by A. K. Volkov, D. V. Aidarkin, A. K. Volkov

“…Х-ray image based factors are the specific properties of the x-ray image that influence the ability to detect prohibited items by aviation security screeners. …”
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MVSAPNet: A Multivariate Data-Driven Method for Detecting Disc Cutter Wear States in Composite Strata Shield Tunneling by Yewei Xiong, Xinwen Gao, Dahua Ye

“…To address the problem of imbalance in the wear data, a prototype network is used to learn the centers of the normal and wear state classes, and the detection of the wear state is achieved by detecting high-dimensional features and comparing their distances to the class centers. …”
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FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…Furthermore, the Dynamic Inter-Domain Feature Fusion module (DIFF) is introduced, which uses large-kernel deep convolution and Hadamard to enable the adaptive fusion of features from different domains, thus addressing the problem of difficult feature fusion due to domain differences. …”
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