BCSM-YOLO: An Improved Product Package Recognition Algorithm for Automated Retail Stores Based on YOLOv11 by Pingqing Hou, Shaoze Huang

“…Firstly, introducing the Space-to-Depth Convolution (SPD-Conv) can maximize the preservation of detailed information such as commodity texture and shape in the downsampling stage, which provides a rich information base for the subsequent feature extraction. Then, the Convolutional Block Attention Module (CBAM) screens the processed data, adaptively focuses on the key regions, and suppresses the background interference. …”
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Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…Secondly, an efficient multi-scale attention mechanism, EMA (Efficient Multi-Scale Attention Module), based on cross-space learning is integrated into the FPN (Feature Pyramid Network) part of the model. This mechanism highlights target features while suppressing background interference. …”
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Phase Demodulation of Short-Cavity Fabry–Perot Interferometric Acoustic Sensors With Two Wavelengths by Hao Liao, Ping Lu, Li Liu, Shun Wang, Wenjun Ni, Xin Fu, Deming Liu, Jiangshan Zhang

“…A multichannel tunable optical filter is employed, which selects out two monochromatic beams from the broadband interference spectrum of EFPI with fixed wavelength interval. …”
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Novel Deep Learning Framework for Evaporator Tube Leakage Estimation in Supercharged Boiler by Yulong Xue, Dongliang Li, Yu Song, Shaojun Xia, Jingxing Wu

“…However, leakage faults of evaporation tubes feature high time dependency, strong coupling among monitoring parameters, and interference from noise. …”
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Development of a Multi-Channel Ultra-Wideband Electromagnetic Transient Measurement System by Shaoyin He, Xiangyu Chen, Bohao Zhang, Liang Song

“…It requires that the electric field sensor has features such as a large dynamic measurement range (amplitude from hundreds of V/m to tens of kV/m), a fast response speed (response time in the order of nanoseconds or sub-nanoseconds), a wide test bandwidth (DC to 1 GHz even above), miniaturization, and robustness to strong electromagnetic interference. …”
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Optimal Design of a Sensor Network for Guided Wave-Based Structural Health Monitoring Using Acoustically Coupled Optical Fibers by Rohan Soman, Jee Myung Kim, Alex Boyer, Kara Peters

“…In the second stage, an acoustic coupler network is designed to ensure high-fidelity measurements with minimal interference from other bond locations (overlap of measurements) as well as interference from features in the acoustically coupled circuit (fiber end, coupler, etc.). …”
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Research on multi-user identity recognition based on Wi-Fi sensing by Zhongcheng WEI, Wei CHEN, Yanhu DONG, Bin LIAN, Wei WANG, Jijun ZHAO

“…With the advancement of wireless sensing technology, research on Wi-Fi-based identity recognition has garnered significant attention in fields such as human-computer interaction and home security.While identity recognition based on Wi-Fi signals has achieved initial success, it is currently primarily suitable for scenarios involving individual user behavior.Identity recognition for multiple users in concurrent behavior scenarios still faces a series of challenges, including issues related to mutual interference between users and poor model robustness.Therefore, a Wiblack system for recognizing multiple user identities in a concurrent distribution behavior scenario was proposed.The core idea was to train a multi-branch deep neural network (Wiblack-Net) to extract unique features for each individual user.Firstly, the common features among multiple users were extracted using the backbone network.Then, a binary classifier was assigned to each user to determine the presence of the target user within a given group, thereby achieving identity recognition for multiple users based on concurrent behavior.In addition, experiments comparing Wiblack with several independent binary classification models and a single multiclassification model were conducted to analyze operational efficiency.System performance experimental results demonstrate that when simultaneously identifying the identities of three users, Wibalck achieves an average accuracy of 92.97%, an average precision of 93.71%, an average recall of 93.24%, and an average F1 score of 92.43%.…”
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Attention-mechanism-based tracking method for intelligent Internet of vehicles by Xu Kang, Bin Song, Jie Guo, Xiaojiang Du, Mohsen Guizani

“…Aiming at the problem that the traditional convolutional neural network is vulnerable to background interference, this article proposes vehicle tracking method based on human attention mechanism for self-selection of deep features with an inter-channel fully connected layer. …”
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An Improved YOLOv8-Based Dense Pedestrian Detection Method with Multi-Scale Fusion and Linear Spatial Attention by Han Gong, Tian Li, Lijuan Wang, Shucheng Huang, Mingxing Li

“…Simultaneously, a multi-scale linear spatial attention module is designed to amplify features of visible parts of occluded pedestrians while suppressing interference from complex backgrounds. …”
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Synthetic and cosmological axion hybridization: Entangled photons, Hanbury Brown–Twiss, and quantum beats by Daniel Boyanovsky

“…The final two-photon state features both kinematic and polarization entanglement and displays quantum beats as a consequence of the interference between the decay paths. …”
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Camera-Adaptive Foreign Object Detection for Coal Conveyor Belts by Furong Peng, Kangjiang Hao, Xuan Lu

“…CAFOD incorporates three main strategies: (1) Multi-View Data Augmentation (MVDA) simulates viewpoint variations during training, enabling the model to learn robust, viewpoint-invariant features; (2) Context Feature Perception (CFP) integrates local coal background information to reduce false detections outside the conveyor belt; and (3) Conveyor Belt Area Loss (CBAL) enforces explicit attention to the conveyor belt region, minimizing background interference. …”
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A Novel Lightweight U-Shaped Network for Crack Detection at Pixel Level by Zhong Luo, Xinle Li, Yanfeng Zheng

“…Meanwhile, a coordinate-aware fusion module (CFM) is proposed, which fully fuses skip connection features and decoder features to enhance cross-channel interaction information. …”
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A Novel Few-Shot Learning Framework Based on Diffusion Models for High-Accuracy Sunflower Disease Detection and Classification by Huachen Zhou, Weixia Li, Pei Li, Yifei Xu, Lin Zhang, Xingyu Zhou, Zihan Zhao, Enqi Li, Chunli Lv

“…The rapid advancement in smart agriculture has introduced significant challenges, including data scarcity, complex and diverse disease features, and substantial background interference in agricultural scenarios. …”
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Deblurring Method of Face Recognition AI Technology Based on Deep Learning by Weilong Li, Jie Li, Junhui Zhou

“…As a common method of deep learning, a convolutional neural network (CNN) shows excellent performance in face recognition. The features extracted by traditional face recognition methods are greatly influenced by subjective factors and are time-consuming and laborious. …”
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Research and application of micro-scale fracture prediction technology for deep coalbed methane based on five-dimensional seismic data by Lei ZHANG, Fengyin XU, Jiangnan TONG, Feng ZHANG, Feng WANG, Wei HOU, Yihang CHANG, Songyi HOU, Xiangbing PEI, Zhenyi CAO, Tong CHEN, Xuefeng LI, Ke ZHOU, Yongzhou LI, Huaibin ZHEN, Wenting ZENG

“…Through precise 3D seismic interpretation in the early stage, it was found that faults were not developed in the block, suggesting that the development of local micro-scale fractures might be a significant factor causing fracturing interference in horizontal wells. Focusing on the deep No. 8 coal seam in the study area, we rely on high-quality 3D seismic data characterized by “two wide and one high” features. …”
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Utilizing GCN-Based Deep Learning for Road Extraction from Remote Sensing Images by Yu Jiang, Jiasen Zhao, Wei Luo, Bincheng Guo, Zhulin An, Yongjun Xu

“…These high-dimensional features are then segmented, and enhanced channel and spatial features are obtained via attention mechanisms, effectively mitigating background interference and intra-class ambiguity. …”
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A Mechanical Fault Identification Method for On-Load Tap Changers Based on Hybrid Time—Frequency Graphs of Vibration Signals and DSCNN-SVM with Small Sample Sizes by Yanhui Shi, Yanjun Ruan, Liangchuang Li, Bo Zhang, Yichao Huang, Mao Xia, Kaiwen Yuan, Zhao Luo, Sizhao Lu

“…Secondly, these time–frequency graphs are input into the CNN to extract key features. In the fusion layer, the feature vectors from the STFT and SWT graphs are combined to form a fusion vector that encompasses both global and local time–frequency features. …”
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A Machine Learning-Based Method for Pig Weight Estimation and the PIGRGB-Weight Dataset by Xintong Ji, Qifeng Li, Kaijun Guo, Weihong Ma, Mingyu Li, Zhankang Xu, Simon X. Yang, Zhiyu Ren

“…Regression models, including the BPNN with Trainlm, are used to predict pig weight based on the extracted features, achieving the best performance in our experiments. …”
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RETRACTED: Standards for ensuring the legality of covert activities in criminal proceedings through the prism of European Court of Human Rights by O. V. Kaplina, A. R. Tumanyants, I. O. Kritskaya

“…The formal-legal (legal-technical) method was used to study the rules of law, to analyze the features of legal technique; and the hermeneutical method revealed the legal content of the norms, legislative proposals and defects in legal regulation. …”
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A Composite Recognition Method Based on Multimode Mutual Attention Fusion Network by Xing Ding, Xiangrong Zhang, Chao Liang, Bo Liu, Lanjie Niu

“…The test results show that the multimode mutual attention fusion network containing a feature fusion attention mechanism has the highest detection performance and anti-interference ability. …”
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