Research on Target Detection Algorithm for Solder Joint Defects Based on the Improved YOLOv8 by Chengkai Zhang, Xiaocui Feng, Pujun Mao, Fuyan Lv

“…Aiming at the problem of low accuracy in solder joint defect detection caused by the complex background and difficult to extract defect features of circuit boards using through-hole technology (THT), an improved YOLOv8 solder joint defect target detection algorithm was proposed. …”
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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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Enhancing Fake Review Detection Using Linguistic Exaggeration, BERT Embeddings, and Fuzzy Logic by Mohammed Ennaouri, Ahmed Zellou

“…However, the presence of fake reviews threatens the credibility of review platforms, which requires advanced detection mechanisms. The core objective of this work is to develop a hybrid model that combines interpretable handcrafted linguistic cues with deep semantic features for more accurate, robust, and accurate fake review detection. …”
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Dual-Branch Multi-Dimensional Attention Mechanism for Joint Facial Expression Detection and Classification by Cheng Peng, Bohao Li, Kun Zou, Bowen Zhang, Genan Dai, Ah Chung Tsoi

“…This paper addresses the central issue arising from the (SDAC) of facial expressions, namely, to balance the competing demands of good global features for detection, and fine features for good facial expression classifications by replacing the feature extraction part of the “neck” network in the feature pyramid network in the You Only Look Once X (YOLOX) framework with a novel architecture involving three attention mechanisms—batch, channel, and neighborhood—which respectively explores the three input dimensions—batch, channel, and spatial. …”
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An improve fraud detection framework via dynamic representations and adaptive frequency response filter by Juncheng Yang, Shuxia Li, Zijun Huang, Junhang Wu

“…Additionally, in LSN learning, we designed a trainable filter to capture differences between feature channels during information aggregation, mitigating the over-smoothing problem. …”
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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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Incipient Fault Detection of Rolling Element Bearings Based on Deep EMD-PCA Algorithm by Huaitao Shi, Jin Guo, Zhe Yuan, Zhenpeng Liu, Maxiao Hou, Jie Sun

“…Due to the relatively weak early fault characteristics of rolling bearings, the difficulty of early fault detection increases. For unsolving this problem, an incipient fault detection method based on deep empirical mode decomposition and principal component analysis (Deep EMD-PCA) is proposed. …”
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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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A Tank Experiment of the Autonomous Detection of Seabed-Contacting Segments for Submarine Pipelaying Operations by Bo Wang, Jie Wang, Chen Zheng, Ye Li, Jian Cao, Yueming Li

“…Due to the weak structural features of pipelines and underwater light attenuation, the complex and harsh environment of the seabed greatly increases the possibility of an underwater autonomous remotely operated vehicle losing a detected seabed-contacting segment during pipe-laying operations. …”
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MEIS-YOLO: Improving YOLOv11 for efficient aerial object detection with lightweight design by Yicheng Liu, Jinsong Wu, Li Chen

“…The core innovation of the model lies in the introduction of a Multi-scale Edge Information Selection (MEIS) module, which selects key features highly relevant to the target detection task from multi-scale features, strengthening the representation of edge information and significantly improving detection performance under conditions of small targets and complex backgrounds. …”
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Hyperspectral Target Detection Based on Macro–Micro Spectrum Contrastive Learning by Jiacheng Tian, Dunbin Shen, Wenfeng Kong, Min Li, Hongyu Wang, Xiaorui Ma

“…Depending on single target example under the influence of spectral variation, deep learning-based hyperspectral target detection (HTD) methods are challenged by the problem of insufficient target knowledge. …”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…The existing research on voice-based depression detection has many problems, such as complicated feature extraction, single data expansion and uncontrollable prediction bias in regression prediction. …”
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Text-Guided Distribution Calibration for Few-Shot Object Detection in Remote Sensing Images by Yu Cao, Jingyi Chen, Haoyu Wang, Lei Zhang, Chen Ding, Wei Wei, Shiqi Cao, Meilin Xie

“…Considering the limited visual information of the novel classes, we propose a cross-modal knowledge transfer strategy, which aims to extract the corresponding text feature of the object class name through a multimodal pretraining model CLIP and transfer the text knowledge to the FSOD model, to mitigate the feature bias problem. …”
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A novel temporal classification prototype network for few-shot bearing fault detection by Yanfei Liu, Ziang Du, Hao Zheng, Qian Zhang, Cheng Chen, Nana Wu

“…At present, the problem of less fault data samples in the field of fault detection has caused great trouble to the research of deep learning. …”
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A Spatio-Temporal Attention Network With Multiframe Information for Infrared Small Target Detection by Donghui Liu, Wenlong Zhang, Zicheng Feng, Xiaoliang Sun, Rui Zhang, Yang Shang

“…Most algorithms focus solely on extracting features from the spatial domain. However, this approach often leads to suboptimal detection performance. …”
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Developing an innovative lung cancer detection model for accurate diagnosis in AI healthcare systems by Wang Jian, Amin Ul Haq, Noman Afzal, Shakir Khan, Hadeel Alsolai, Sultan M. Alanazi, Abu Taha Zamani

“…Abstract Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. …”
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Research on Face Local Attribute Detection Method Based on Improved SSD Network Structure by Qun Luo, Zhendong Liu

“…The existing face detection methods usually had the problem of low accuracy of face recognition in the environment of occlusion interference, which was limited when applied to the face detection task in complex scenes. …”
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Face Detection Method based on Lightweight Network and Weak Semantic Segmentation Attention Mechanism by Xiaoyan Wu

“…A face detection method based on lightweight network and weak semantic segmentation attention mechanism is proposed in this paper, aiming at the problems of low detection accuracy and slow detection speed in face detection in complex scenes. …”
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Intelligent Recognition and Parameter Estimation of Radar Active Jamming Based on Oriented Object Detection by Jiawei Lu, Yiduo Guo, Weike Feng, Xiaowei Hu, Jian Gong, Yu Zhang

“…The core idea of the method is to reformulate the jamming perception problem as an object detection task in computer vision, and we pioneer the application of oriented object detection to this problem, enabling simultaneous jamming classification and key parameter estimation. …”
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Simultaneous vehicular location and velocity detection towards 6G integrated communication and sensing by Bingpeng ZHOU, Shanshan MA

“…., signal bandwidth, the number of transceiver antenna and sub-carriers, on RSS performance was evaluated as well.It was verified by simulations that the proposed RSS algorithm outperformed state-of-the-art baseline methods due to the employed problem-specific system design.In addition, it was shown by simulations that the achieved RSS error was reduced with the increasing of sub-carrier frequency, the number of transceiver antennas and sub-carriers, and it was increased with the increasing distance between base station and vehicle receiver.Particularly, the vehicle location estimation accuracy was increasing with system bandwidth, but it was invariant with central carrier frequency, since only baseband features of received signal were employed for vehicle localization.In contrast, the vehicle velocity detection accuracy was increasing with central carrier frequency, yet it was insensitive to system bandwidth, given the fixed number of sub-carriers.…”
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