Experimental Study of Trajectory Features for the Recognition of Low-Flying Low-Speed Radar Targets Using Passive Coherent Radar Systems by V. L. Dao, A. A. Konovalov, M. H. Le

“…In a search for new solutions to the problem of recognizing small UAVs, trajectory features can be used.Aim. …”
Get full text

Intelligent Fault Severity Detection of Rotating Machines Based on VMD-WVD and Parameter-Optimized DBN by Ning Jia, Yao Cheng, Youyuan Tian, Feiyu Yang

“…An intelligent fault severity detection method based on variational mode decomposition- (VMD-) Wigner-Ville distribution (WVD) and sparrow search algorithm- (SSA-) optimized deep belief network (DBN) is suggested to address the problem that typical fault diagnostic algorithms are inappropriate for extremely comparable vibration signals when the samples are insufficient. …”
Get full text

Salient object detection dataset with adversarial attacks for genetic programming and neural networksMendeley Data by Matthieu Olague, Gustavo Olague, Roberto Pineda, Gerardo Ibarra-Vazquez

“…Machine learning is central to mainstream technology and outperforms classical approaches to handcrafted feature design. Aside from its learning process for artificial feature extraction, it has an end-to-end paradigm from input to output, reaching outstandingly accurate results. …”
Get full text

Detection of the Pin Defects of Power Transmission Lines Based on Improved TPH-MobileNetv3 by Mengxuan Li, Jingshan Han, Zhi Yang, Bin Zhao, Peng Liu

“…Given the small size of a pin and many similar components, the detection of such defects is not ideal, which is a technological problem in the identification and diagnosis of power defects. …”
Get full text

Deep learning-based automatic detection and grading of disk herniation in lumbar magnetic resonance images by Yan Guo, Xiaoxiang Huang, Wei Chen, Ichiro Nakamoto, Weiqing Zhuang, Hua Chen, Jie Feng, Jianfeng Wu

“…The ECA module optimizes the weights of the feature channels and enhances the sensitivity of detection for small-target lesions, and the mAP50 was improved by 4.4% compared with that of YOLOv8. …”
Get full text

Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

“…Depression is a significant mental health problem and presents a challenge for the machine learning field in the detection of this illness. …”
Get full text

YOLO-Helmet: A Novel Algorithm for Detecting Dense Small Safety Helmets in Construction Scenes by Guoliang Yang, Xinfang Hong, Yangyang Sheng, Liuyan Sun

“…Firstly, in order to solve the problem of difficult detection due to the small area of the helmet in the image, a small size detection layer was extended to improve the detection sensitivity of the network to small size targets. …”
Get full text

RT-DETR-Pro: An Enhanced RT-DETR Model for Visual Detection of Photovoltaic Module Defects by Yunliang Chen, Mingtao Shan, Wei Zhou, Bing Ma, Xun Mei

“…An enhanced RT-DETR (Real-Time Detection Transformer) model, RT-DETR-Pro, is proposed to address the problem of low recognition rates for visual detection of PV (photovoltaic) module defects by traditional object detection methods. …”
Get full text

Infrared object detection for robot vision based on multiple focus diffusion and task interaction alignment by Jixu Zhang, Li Wang, Hung-Wei Li, Meng-Yen Hsieh, Shunxiang Zhang, Hua Wen, Meng Chen

“…However, the small gray-scale difference between the object and the background region in the infrared grayscale image and the single gray-scale information lead to the blurring of the semantic information of the image, which makes the robot unable to detect the object effectively. To address the above problems, this paper proposes a robot visual infrared object detection (MFDTIA-Detection) based on multiple focus diffusion and task interaction alignment. …”
Get full text

A security data detection and management method in digital library network based on deep learning by Diyin Zhu, Yihang Wei, Jiali Cai, Jingwen Wang, Zhongshan Chen

“…With the rapid growth of data volume in digital library and the increasingly complex network environment, traditional network security measures are no longer able to meet their security needs. In response to the problems of low detection accuracy and long detection time in traditional network security methods, we propose a digital library network security data detection and management method based on bidirectional gated recurrent unit and temporal convolutional network detector (BiGRU-TCNDetector) using the powerful capabilities of deep learning technology. …”
Get full text

Detection of weeds in teff crops using deep learning and UAV imagery for precision herbicide application by Alemu Setargew Kebede, Tsehay Wasihun Muluneh, Abebe Belay Adege

“…This study introduces an optimized deep learning model for weed detection in Teff fields, enabling selective and efficient herbicide application through unmanned aerial vehicles (UAVs). …”
Get full text

High resolution weld semantic defect detection algorithm based on integrated double U structure by Xiaoyan Li, Yi Wei, Zhigang Lv, Peng Wang, Liangliang Li, Mengyu Sun, Chu Wang

“…Then, a multi-image hybrid stitching technology was proposed to reconstruct the long weld into a standard size of 1500 × 1500, which not only expanded the WSCR data set, but also effectively improved the data imbalance problem. In terms of model architecture, by improving U2Netp and UNet networks, MC-SPP module (multi-connection spatial pyramid pooling), RMAG module (residual multi-add gating recurrent unit), HDC-CBAM module (hybrid dilated convolution-convolutional block attention) and CCM module (cross-layer connection fusion) were integrated to form a cascade network with multi-level feature fusion capability. …”
Get full text

Power Corridor Safety Hazard Detection Based on Airborne 3D Laser Scanning Technology by Shuo Wang, Zhigen Zhao, Hang Liu

“…The results of detecting these five transmission lines reveal 54 general hazards, 22 major hazards, and an emergency hazard in terms of hazards of the vegetation type. …”
Get full text

A novel and efficient personalized stress detection technique using a deep learning model by Ulligaddala Srinivasarao, Gopisetty Rathnamma, M. Satish Kumar, Lakshmipathi Anantha, Rakesh Kumar Donthi, T. Jhansi Rani

“…It majorly affects adults and elders, which further leads to chronic health problems and heart-related diseases. Various techniques were developed to detect stress levels. …”
Get full text

Blockchain enhanced distributed denial of service detection in IoT using deep learning and evolutionary computation by V. V. S. H. Prasad, Swathi Sowmya Bavirthi, C. S. S. Anupama, E. Laxmi Lydia, K. Sathesh Kumar, Khalid Ammar, Mohamad Khairi Ishak

“…As a developing technology, BC holds the possibility of resolving security problems in IoT. This paper proposes the Metaheuristic-Optimized Blockchain Framework for Attack Detection using a Deep Learning Model (MOBCF-ADDLM) method. …”
Get full text

Comparative analysis of single-board computers for the development of a microarchitectural computing system for fire detection by D. A. Paulenka

Get full text

Improving outcomes for people with autism spectrum disorders by reducing mental health problems: the IAMHealth research programme including one RCT by Emily Simonoff, Gillian Baird, Bryony Beresford, Tony Charman, Martin Knapp, Andrew Pickles, Carol Povey, Tom Purser, Paramala Santosh, Vicky Slonims, Stephen Scott

“…Design Work package 1: we developed and validated a new instrument to provide improved detection of mental health and behavioural problems in autistic people from childhood through to adult life. …”
Get full text

Unmanned aerial vehicle based multi-person detection via deep neural network models by Mohammed Alshehri, Laiba Zahoor, Yahya AlQahtani, Abdulmonem Alshahrani, Dina Abdulaziz AlHammadi, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

Get full text

Xq12q13.2 duplication detected in a child in selective exome screening by A. A. Dokshukina, Je. Shubina, D. N. Maslennikov, I. O. Sadelov, E. R. Tolmacheva, S. V. Ionushene, T. A. Bairova, L. V. Rychkova, D. Yu. Trofimov, D. N. Degtyarev

Get full text

CBSNet: An Effective Method for Potato Leaf Disease Classification by Yongdong Chen, Wenfu Liu

“…As potato is an important crop, potato disease detection and classification are of key significance in guaranteeing food security and enhancing agricultural production efficiency. …”
Get full text