Defect intelligent recognition of membrane product based on deep learning by Maonian Wu, Ling Li, Wei Peng, Tao Wu, Jinwei Yu, Bo Zheng, Shaojun Zhu

“…We present a feature enhancement module called the SE-CAR, which aims to handle the identified problems effectively. …”
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E-FCNN Based Electric Power Inspection Image Enhancement by Wanrong BAI, Xun ZHANG, Xiaoqin ZHU, Jixiang LIU, Qiyu CHENG, Yan ZHAO, Jie SHAO

“…In order to solve this problem, we propose an edge-aware feedback convolutional neural network (E-FCNN), which not only adds Resnet blocks and feedback mechanism to the conventional super-resolution network to strengthen the ability of feature extraction, but also adds texture information to the edge-aware branch to enhance the image detail. …”
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Predictors of Sudden Cardiac Death during Extracardiac Surgical Interventions by L. A. Maltseva, N. V. Krasnenko, V. V. Khalimonchik, R. A. Shkapyak

“…A number of the drugs that are most frequently used in anesthesiology and negative affect the myocardium and systemic hemodynamics are listed, which is extremely important to patients having initially cardiovascular diseases. The detection of the predictors of SCD in the preop-erative period and the methods of studying the patients, among which scale, instrumental, and biochemical methods being emphasized, feature in the paper. …”
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Efficient Brain Tumor Segmentation for MRI Images Using YOLO-BT by Mengying Xiong, Aiping Wu, Yue Yang, Qingqing Fu

“…Aiming at the problems of inaccurate segmentation and low detection efficiency caused by irregular tumor shape and large size differences in brain MRI images, this study proposes a brain tumor segmentation algorithm, YOLO-BT, based on YOLOv11. …”
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Family violence against children: intervention of nurses from the Family Health Strategy by Kelianny Pinheiro Bezerra, Akemi Iwata Monteiro

“…Health promotion actions are educational activities developed after detecting the problem. Fear of reprisals by the offending agent, work overload, lack of managerial support and the difficulty for the accomplishment of interdisciplinarity, intersectorality and comprehensive care were mentioned as barriers to the confrontation of the problem.…”
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On OCT Image Classification via Deep Learning by Depeng Wang, Liejun Wang

“…In this paper, an automatic method based on deep learning is proposed to detect AME and AMD lesions, in which two publicly available OCT datasets of retina were adopted and a network model with effective feature of reuse feature was applied to solve the problem of small datasets and enhance the adaptation to the difference of different datasets of the approach. …”
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Pattern transition recognition based on transfer learning for exoskeleton across different terrains by Yifan Gao, Jianbin Zheng, Yang Gao, Ziyao Chen, Jing Tang, Liping Huang

“…The accuracy of pattern transition detection reaches 97.46%, 97.62%, and 98.21% in M0, M20, and M40, respectively. …”
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A Deep Learning Approach for Crop Disease and Pest Classification Using Swin Transformer and Dual-Attention Multi-Scale Fusion Network by R. Karthik, Armaano Ajay, Akshaj Singh Bisht, T. Illakiya, K. Suganthi

“…Deep learning offers a fast and accurate solution to this problem by automating the process of disease and pest detection. …”
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Development and Investigation of Vision System for a Small-Sized Mobile Humanoid Robot in a Smart Environment by Amer Tahseen Abu-Jassar, Hani Attar, Ayman Amer, Vyacheslav Lyashenko, Vladyslav Yevsieiev, Ahmed Solyman

“…A structure of information interaction between hardware modules is proposed, and a connection scheme is developed, on the basis of which a model of a computer vision system is assembled for research, with the required algorithmic and software for solving the problem. To ensure the high speed of the computer vision system based on the ESP32-CAM module, the neural network was improved by replacing the Visual Geometry Group 16 (VGG-16) network as the base network for extracting the functions of the Single Shot Detector (SSD) network model with the tiny-YOLO lightweight network model, which made it possible to preserve the multidimensional structure of the network model feature graph, resulting in increasing the detection accuracy, while significantly reducing the amount of calculations generated by the network operation, thereby significantly increasing the detection speed, due to a limited set of objects. …”
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Improving the Incident Management Process Based on a Use Case Approach by A. A. Mikryukov, A. V. Kuular

“…The article considers the process approach to incident management in case of technical failures and its main stages: detection, response, investigation, elimination, resolution. …”
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Research on Autonomous Positioning Method for Inspection Robot Based on Distributed 2D LiDARs by Feng Yun Huang, Jun Qiang Liu, De Hao Fang

“…To address the positioning problem during autonomous operation process under the automated vehicle inspection scenario for annual vehicle inspections. …”
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High-Quality Multispectral Image Reconstruction for the Spectral Camera Based on Ghost Imaging via Sparsity Constraints Using CoT-Unet by Tao Hu, Jianxia Chen, Shu Wang, Jianrong Wu, Ziyan Chen, Zhifu Tian, Ruipeng Ma, Di Wu

“…To solve the problem of poor quality in ghost imaging via sparsity constraints (GISC) multispectral image reconstruction with correlation operations and compressed sensing algorithms under low sampling rate detection conditions, we propose an end-to-end deep-learning-based method. …”
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Deep learning approach with ConvNeXt-SE-attn model for in vitro oral squamous cell carcinoma and chemotherapy analysis by Abhay Nath, Om Roy, Priyanka Silveri, Sanskruti Patel

“…The findings are critical to the increased feature-representation power and the robustness of classification of the architecture.The proposed architecture employs ConvNeXt backbone with SE blocks and hybrid attention to extract essential details within class boundaries which standard models usually miss.The activation through Gaussian-based GReLU incorporates Swish activation together with DropPath regularization for producing smooth gradient patterns which lead to generalizable features across imbalanced datasets.Grad-CAM enhances interpretability by showing which image sections lead to predictions in order to enable clinical decisions.The model demonstrates its capability as an effective detection method for minimal variations in oral cells which supports precise non-invasive treatment approaches for OSCC.…”
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Digital security risk identification and model construction of smart city based on deep learning by Zhilei Zhao

“…In order to deal with these problems, this paper designs a flexible three-layer architecture framework, and introduces a new intrusion detection feature selection method that combines flock optimization (CSO) and genetic algorithm (GA) to reduce the complexity of feature selection and enhance the detection and processing power of security vulnerabilities through deep neural networks (DNN). …”
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Fault Diagnosis of Photovoltaic Grid-connected Inverter Based on Wavelet Analysis by FAN Jinglu, YI Yunlan

“…Aiming to the fault detecting of photovoltaic grid-connected inverter and its intelligent online diagnosis problem, it proposed a C3C3 inverter fault feature extraction method, which used a three-phase inverter output current as a result of judgments based on wavelet analysis, and combines the approximate component and detail component of failure signals as failure feature vector; then used the classification of neural network to complete the fault diagnosis of photovoltaic grid inverters. …”
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Learning Transferable Convolutional Proxy by SMI-Based Matching Technique by Wei Jin, Nan Jia

“…Domain-transfer learning is a machine learning task to explore a source domain data set to help the learning problem in a target domain. Usually, the source domain has sufficient labeled data, while the target domain does not. …”
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Ultrastructural analysis of changes in myocardial blood microvessels in severe burn shock by S. V. Savchenko, N. G. Oshchepkova, N. P. Bgatova, Yu. S. Taskaeva, E. V. Kuznetsov, V. P. Novoselov, A. Yu. Letyagin

“…Burn injury is an important medical problem, as it is accompanied by high mortality rates in burn shock. …”
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A swin transformer and CNN fusion framework for accurate Parkinson disease classification in MRI by Sayyed Shahid Hussain, Pir Masoom Shah, Hussain Dawood, Xu Degang, Ahmad Alshamayleh, Muhammad Adnan Khan, Taher M. Ghazal

“…Convolutional neural networks (CNNs) have been extensively employed in Parkinson’s disease (PD) detection using MR images. However, CNN models generally focus on local features while prone to capture global representations. …”
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Using Partial Differential Equation Face Recognition Model to Evaluate Students’ Attention in a College Chinese Classroom by Xia Miao, Ziyao Yu, Ming Liu

“…The partial differential equation learning model is applied to another high-level visual-processing problem: face recognition. A novel feature selection method based on partial differential equation learning model is proposed. …”
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DDANet: A deep dilated attention network for intracerebral haemorrhage segmentation by Haiyan Liu, Yu Zeng, Hao Li, Fuxin Wang, Jianjun Chang, Huaping Guo, Jian Zhang

“…Additionally, the authors incorporate a self‐attention mechanism to capture global semantic information of high‐level features to guide the extraction and processing of low‐level features, thereby enhancing the model's understanding of the overall structure while maintaining details. …”
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