Detection algorithm for wearing safety helmet under mine based on improved YOLOv5s by Yuanbin WANG, Sixiong WEI, Huaying WU, Yu DUAN, Meng LIU

“…Aiming at the problems of low accuracy and high missed detection rate of personnel safety helmet detection algorithm caused by complex environment under mine, an improved mine safety helmet detection algorithm based on YOLOv5s is proposed. …”
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A systematic review of machine learning and deep learning approaches in plant species detection by Deepti Barhate, Sunil Pathak, Bhupesh Kumar Singh, Amit Jain, Ashutosh Kumar Dubey

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A NOVEL VOICE-BASED SYSTEM FOR PARKINSON’S DISEASE DETECTION USING RNN-LSTM by Repudi Pitchiah, T. Sasi Rooba, Uma Pavan Kumar

“…Importantly, Deep Neural Networks have become the best classification tool for PD detection even without the use of a feature selection strategy. …”
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Towards precision agriculture tea leaf disease detection using CNNs and image processing by Irfan Sadiq Rahat, Hritwik Ghosh, Suresh Dara, Shashi Kant

“…Key to our model’s design is the incorporation of residual blocks, facilitating the learning of deeper networks by alleviating the vanishing gradient problem. These blocks combine Conv2D layers, batch normalization, activation layers, and shortcut connections, ensuring robust and efficient feature extraction at various levels of abstraction. …”
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Fault Location on Radial Distribution Systems Using Wavelets and Artificial Neural Networks with a New Data Processing Feature by NERI Jr., A. L., MOREIRA, F. A., de SOUZA, B. A.

“…Under permanent fault conditions, maintenance crew has the duty to detect the problem, repair the defect and recover the power supply system. …”
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Distributed denial-of-service (DDOS) attack detection using supervised machine learning algorithms by S. Abiramasundari, V. Ramaswamy

“…DDoS attacks need to be detected since they cause serious problems. Supervised machine learning models are effective mechanisms for detecting DDoS attacks. …”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…First, based on the YOLOv7-Tiny network, the MAFPN neck structure is used to replace the ELAN structure to achieve the multi-scale capture of semantic information of underwater sea treasures, and to enhance the UPA-YOLO model to accurately locate the targets of underwater sea treasures; second, the P2ELAN module is constructed and added to the backbone network, which makes use of the redundancy information in the feature map and dynamically adjusts the convolution kernel to adapt to data The P2ELAN module is added to the backbone network, using the redundant information in the feature map, dynamically adjusting the convolutional kernel to adapt to the lack of data, reducing the number of parameters in the model, and introducing the MSCA attention mechanism to inhibit the complex and changeable background features underwater, to improve the semantic feature extraction ability of the UPA-YOLO model for underwater targets, adding the MPDiou loss function to the improved algorithm model and completing the data validation of the detection model; finally, based on the TensorRT acceleration framework, the optimisation of the target detection Finally, based on the TensorRT acceleration framework, the target detection model is optimised, and the Jetson Nano edge device is used to complete the localisation deployment and realise the real-time target detection task of underwater sea treasures. …”
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An Attention-Based Spatial-Spectral Joint Network for Maize Hyperspectral Images Disease Detection by Jindai Liu, Fengshuang Liu, Jun Fu

“…However, the abundance of redundant information in hyperspectral data poses challenges in extracting significant features. To overcome the above problems, in this study we proposed an attention-based spatial-spectral joint network model for hyperspectral detection of pest-infected maize. …”
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Domain Diversification Progressive Cross-Domain Weakly-Supervised Real-time Object Detection by LI Chengyan, ZHENG Qisen, WANG Hao

“…Aiming at the problems of large image translation bias at the pixel-level adaptation, the risk of source-bias discrimination at the feature-level adaptation, and the inability of weakly supervised learning to balance detection accuracy and real- time performance, a diversified domain shifter and pseudo bounding box generator are proposed to gradually adjust the pre-training 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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Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…Early mental disorder detection can reduce costs for public health agencies and prevent other major comorbidities. …”
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Obstacle Feature Information-Based Motion Decision-Making Method for Obstacle-Crossing Motions in Lower Limb Exoskeleton Robots by Yuepeng Zhang, Guangzhong Cao, Jun Wu, Bo Gao, Linzhong Xia, Chen Lu, Hui Wang

“…To overcome the problem of insufficient adaptability to the motion environment of lower limb exoskeleton robots, this paper introduces computer vision technology into the motion control of lower limb exoskeleton robots and studies an obstacle-crossing-motion method based on detecting obstacle feature information. …”
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AnoViT: Unsupervised Anomaly Detection and Localization With Vision Transformer-Based Encoder-Decoder by Yunseung Lee, Pilsung Kang

“…Image anomaly detection problems aim to determine whether an image is abnormal, and to detect anomalous areas. …”
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Fusion of non-iterative deep neural network feature extraction with kernel extreme learning machine for plant disease classification by Kirti Kirti, Navin Rajpal, Virendra P. Vishwakarma, Pramod Kumar Soni

“…Abstract Plant disease identification and detection refer to the process of recognizing and diagnosing diseases that affect plants. …”
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Specific Features of Interaction between Criminal Police Divisions and Other Subjects within Counteracting Criminal Offenses against Morality by O. M. Yemets

“…During the research the author has used the system of methods of scientific cognition: formal logic (abstraction, analogy, deduction, induction, synthesis) for the detailed clarification of the content of the considered issues; empirical – during the experimental study; method of system analysis – to determine the directions of introduction of innovative approaches to solve the problem; theoretical – during the study of scientific and educational literature; modeling – in the study of certain objects by modeling their individual features. …”
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AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…The key problem lies in the underreporting and delayed detection of Adverse Drug Reactions (ADRs) due to the heterogeneous nature of medical data, class imbalance, and the limited scope of traditional monitoring techniques. …”
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Evaluating the Effectiveness of Image Processing in the Task of Detecting Moving Objects by an Optoelectronic Surveillance System by E. I. Mikhnionok, A. V. Khizniak

“…The problem considered by the authors, assessing the effectiveness of the developed image processing method in relation to the problem of detecting moving objects by an optoelectronic surveillance system, determines the need for its consideration in two directions. …”
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Enhanced YOLOv8-based pavement crack detection: A high-precision approach. by ZuXuan Zhang, HongLi Zhang, TongJia Zhang

“…At present, the repair of cracks is still implemented manually, which has the problems of low identification efficiency and high labor cost. …”
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Onboard LiDAR–Camera Deployment Optimization for Pavement Marking Distress Fusion Detection by Ciyun Lin, Wenjian Sun, Ganghao Sun, Bown Gong, Hongchao Liu

“…Then, the LiDAR–camera deployment problem was mathematically formulated for pavement marking distress fusion detection. …”
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Surface Defect Detection Algorithm for Wind Turbine Blades Based on HSCA-YOLOv7 by Bing LI, Yunshan BAI, Kuan ZHAO, Congbin GUO, Yongjie ZHAI

“…Hybrid spatial channel attention (HSCA) is proposed to capture the global visual scene context, increase the semantic difference between target features and the environment, and solve the problem of inconsistent defect scales in blade images. …”
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