Passive indoor human daily behavior detection method based on channel state information by Xiaochao DANG, Yaning HUANG, Zhanjun HAO, Xiong SI

“…The daily behavior detection of indoor human based on CSI is developing rapidly in the field of WSN.At present,most of the research is still in the environment of 2.4 GHz,so the detection rate,robustness and overall performance still need to be improved.In order to solve this problem,a passive indoor human behavior detection method HDFi (Human Detection with Wi-Fi) based on CSI signal was proposed.The method was used to detect the indoor human daily behavior in a 5 GHz band environment,which was divided into three steps:data acquisition,data processing,feature extraction,online detection.Firstly,the experiment collected typical daily behavioral data in complex laboratory and relatively empty meeting room.Secondly,the amplitude and phase data with more obvious features were extracted and processed by low-pass filtering to obtain a set of stable and noise-free data,and then the fingerprint database was established effectively.Finally,in the real-time detection stage,the collected data features were classified by SVM algorithm to extract more stable eigenvalues,and a classification model of indoor human daily behavior detection was established,and then matched the data in the fingerprint database.The experimental results show that the proposed method has the characteristics of high efficiency,high precision and good robustness,and the method does not need any testing personnel to carry any electronic equipment,so it has high practicability.…”
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High catalytic nickel-platinum nanozyme enhancing colorimetric detection of Salmonella Typhimurium in milk by Jie Zhu, Lingyue Xu, Junlin Zhang, Yuxin Wang, Hongyue Yu, Chuanchuan Hao, Guohui Cheng, Daofeng Liu, Minghui Chen

“…Meanwhile, the antibody employed in this NiPt NP-based NLISA exhibits exceptional capture efficacy, generating a stable immune complex with Salmonella Typhimurium. The NiPt NP-based NLISA demonstrates sensitivity, specificity, convenience, and cost-efficiency for the detection of Salmonella Typhimurium. …”
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Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…However, limited computational resources and complex environmental conditions in mine shafts significantly impact the recognition and computational capabilities of detection models. …”
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Unsupervised Hybrid VAE-Based Anomaly Detection for Vehicle Onboard LiDAR Sensors by Nourhen Sboui, Hakim Ghazzai, Mohamed Hadded, Mourad Elhadef, Gianluca Setti

“…The model strikes a good balance between complexity and efficiency, achieving a 10% accuracy improvement compared to existing models, with an accuracy of 95.1% and an F1-score of 82.6%. …”
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Detecting Fraudulent Transactions for Different Patterns in Financial Networks Using Layer Weigthed GCN by Shaziya Islam, Gagan Raj Gupta, Apu Chakraborty, Santosh Singh, Anisha Soni, Chhavi Patle

“…Additionally, the flexible architecture of LayerWeighted-GCN enhances its ability to model complex financial relationships, improving fraud detection accuracy and robustness. …”
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YOLO-Act: Unified Spatiotemporal Detection of Human Actions Across Multi-Frame Sequences by Nada Alzahrani, Ouiem Bchir, Mohamed Maher Ben Ismail

“…This paper introduces YOLO-Act, a novel spatiotemporal action detection model that enhances the object detection capabilities of YOLOv8 to efficiently manage complex action dynamics within video sequences. …”
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Explainable one-class feature extraction by adaptive resonance for anomaly detection in quality assurance. by Hootan Kamran, Dionne Aleman, Chris McIntosh, Tom Purdie

“…We introduce a novel one-class classification framework, using an adaptive neural network architecture, that outperforms both traditional binary and standard one-class classification methods in this imbalanced and complex context, despite the inherent disadvantage of not learning from unacceptable plans. …”
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Automated Surface Crack Identification of Reinforced Concrete Members Using an Improved YOLOv4-Tiny-Based Crack Detection Model by Sofía Rajesh, K. S. Jinesh Babu, M. Chengathir Selvi, M. Chellapandian

“…YOLOv4-tiny is faster and more efficient than its predecessors, offering real-time detection with reduced computational complexity. …”
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Aero-Engine Blade Defect Detection: A Systematic Review of Deep Learning Models by Yusra Abdulrahman, M. A. Mohammed Eltoum, Abdulla Ayyad, Brain Moyo, Yahya Zweiri

“…This is the first systematic review of deep learning models for aero-engine blade defect detection. The findings of this review demonstrate the potential of deep learning in detecting blade defects and improving the accuracy and efficiency of visual inspection. …”
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Adaptive Fusion of LiDAR Features for 3D Object Detection in Autonomous Driving by Mingrui Wang, Dongjie Li, Josep R. Casas, Javier Ruiz-Hidalgo

“…However, traditional early or late fusion methods face challenges such as high bandwidth and computational resources, which make it difficult to balance data transmission efficiency with the accuracy of perception of the surrounding environment, especially for the detection of smaller objects such as pedestrians. …”
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Mitosis detection in histopathological images using customized deep learning and hybrid optimization algorithms. by Afnan M Alhassan, Nouf I Altmami

“…Identifying mitosis is crucial for cancer diagnosis, but accurate detection remains difficult because of class imbalance and complex morphological variations in histopathological images. …”
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Research on the lightweight detection method of rail internal damage based on improved YOLOv8 by Xiaochun Wu, Shuzhan Yu

“…This model offers efficient and reliable technical support for detecting and classifying internal rail damage in rail flaw detection tasks. …”
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Real-Time Runway Detection Using Dual-Modal Fusion of Visible and Infrared Data by Lichun Yang, Jianghao Wu, Hongguang Li, Chunlei Liu, Shize Wei

“…This study proposes a salient object detection (SOD) method that integrates visible and infrared sensors for robust airport runway detection in complex environments. …”
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Method of Calculation of Integrated Performance Indicators of Defense Industry Organizations by S. E. Eroshin

“…The purpose of the study is to develop a parametric monitoring system for defense industry enterprises, optimizing on the principle of minimum sufficiency a set of key indicators of the activities of organizations and increasing the efficiency of management of research institutes, design bureaus, industrial and service enterprises of the military-industrial complex.Materials and methods. …”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Abstract Object detection in remote sensing images is a highly complex and challenging task. …”
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YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model by Nianzu Zhou, Demin Gao, Zhengli Zhu

“…Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses. Existing forest fire detection algorithms face limitations in capturing flame and smoke features in complex natural environments, coupled with high computational complexity and inadequate lightweight design for practical deployment. …”
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Multi-Level Intertemporal Attention-Guided Network for Change Detection in Remote Sensing Images by Shuo Liu, Qinyu Zhang, Yuhang Zhang, Xiaochen Niu, Wuxia Zhang, Fei Xie

“…These methods focus on regions of interest, improving detection accuracy and efficiency. However, external factors can introduce many pseudo-changes, presenting significant challenges for CD. …”
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RS-DETR: An Improved Remote Sensing Object Detection Model Based on RT-DETR by Hao Zhang, Zheng Ma, Xiang Li

“…Recently, deep-learning-based object detection has made significant progress. However, due to large variations in target scale, the predominance of small targets, and complex backgrounds in remote sensing imagery, remote sensing object detection still faces challenges, including low detection accuracy, poor real-time performance, high missed detection rates, and high false detection rates in practical applications. …”
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YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

“…The challenge of efficiently detecting ripe and unripe strawberries in complex environments like greenhouses, marked by dense clusters of strawberries, frequent occlusions, overlaps, and fluctuating lighting conditions, presents significant hurdles for existing detection methodologies. …”
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An adaptive neuro-fuzzy inference scheme for defect detection and classification of solar PV cells by Ranganai Tawanda Moyo, Mendon Dewa, Héctor Felipe Mateo Romero, Victor Alonso Gómez, Jose Ignacio Morales Aragonés, Luis Hernández-Callejo

“…Traditional defect detection and classification methods often face challenges in providing precise and adaptable solutions to this complex problem. …”
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