Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism by Dong Yun Lee, Jang Yeop Kim, Soo Young Cho

“…Sharp and detailed images are essential for accurate diagnoses, but acquiring high-resolution medical images often demands sophisticated and costly equipment. To address this challenge, this study proposes a convolutional neural network (CNN)-based super-resolution architecture, utilizing a melanoma dataset to enhance image resolution through deep learning techniques. …”
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Recognition of Strawberry Powdery Mildew in Complex Backgrounds: A Comparative Study of Deep Learning Models by Jingzhi Wang, Jiayuan Li, Fanjia Meng

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Flat U-Net: An Efficient Ultralightweight Model for Solar Filament Segmentation in Full-disk Hα Images by GaoFei Zhu, GangHua Lin, Xiao Yang, Cheng Zeng

“…In this study, we introduce Flat U-Net, a novel and highly efficient ultralightweight model that incorporates simplified channel attention (SCA) and channel self-attention (CSA) convolutional blocks for the segmentation of solar filaments in full-disk H α images. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…Methods This study proposes a novel computational model: convolutional neural network with Bernoulli random forest for Microbe-Drug Association prediction (CNNBRFMDA). …”
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Recent technological developments allow for passive acoustic monitoring of Orthoptera (grasshoppers and crickets) in research and conservation across a broad range of temporal and... by David Bennett, Henning Nissen, Marc Andre Maschke, Heinrich Reck, Tim Diekötter

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Optimizing AlexNet for accurate tree species classification via multi-branch architecture and mixed-domain attention by Jianjianxian Liu, Tao Xing, Xiangyu Wang

“…The model integrates a multi-branch convolutional module, a mixeddomain attention module, and a joint loss function to improve feature extraction and class separation. …”
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Comparative analysis of data transformation methods for detecting non-technical losses in electricity grids by Maria Gabriel Chuwa, Daniel Ngondya, Rukia Mwifunyi

“…While feature-based detection methods perform well, they often require manual feature engineering and domain expertise. Convolutional neural networks (CNN) have emerged as effective tools for automatically extracting features from raw data, but raw data often lacks the structure needed for optimal feature extraction. …”
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Lightweight visible damage detection algorithm for embedded systems applied to pipeline automation equipment by Jiale Xiao, Lei Xu, Changyun Li, Ling Tang, Guogang Gao

“…This research is designed for low-power, cost-effective and high-performance pipeline defect inspection in embedded systems. …”
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An Approach of Intelligent Compound Fault Diagnosis of Rolling Bearing based on MWT and CNN by Han Tao, Yuan Jianhu, Tang Jian, An Lizhou

“…An approach to intelligent compound fault diagnosis of rolling bearing using multi- wavelet transform（ MWT） and convolution neural network（ CNN） was proposed. According to this approach,the vibration signals of rolling bearing are analyzed by using MWT of removed post processing,and the corresponding multi- wavelet coefficient branches are obtained. …”
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A Surrogate Model for the Rapid Prediction of Factor of Safety in Slopes with Spatial Variability by Xitailang Cao, Shan Lin, Miao Dong, Quanke Hu, Hong Zheng

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Spherical multigrid neural operator for improving autoregressive global weather forecasting by Yifan Hu, Fukang Yin, Weimin Zhang, Kaijun Ren, Junqiang Song, Kefeng Deng, Di Zhang

“…Although methods such as spherical Fourier neural operator (SFNO) based on spherical harmonic convolution can alleviate these problems, they face the challenge of high computational cost. …”
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Analytic Continual Learning-Based Non-Intrusive Load Monitoring Adaptive to Diverse New Appliances by Chaofan Lan, Qingquan Luo, Tao Yu, Minhang Liang, Wenlong Guo, Zhenning Pan

“…Non-intrusive load monitoring (NILM) provides a cost-effective solution for smart services across numerous appliances by inferring appliance-level information from mains electrical measurements. …”
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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

“…Firstly, we propose an efficient mobile inverted bottleneck convolution (EMBC) module for the backbone network. …”
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Low-Latency Neural Network for Efficient Hyperspectral Image Classification by Chunchao Li, Jun Li, Mingrui Peng, Behnood Rasti, Puhong Duan, Xuebin Tang, Xiaoguang Ma

“…Based on this, we introduce a split convolution approach that replaces depthwise convolution, resulting in enhanced arithmetic intensity without significant increase in latency. …”
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Patient-Specific Detection of Atrial Fibrillation in Segments of ECG Signals using Deep Neural Networks by Jeyson A. Castillo, Yenny C. Granados, Carlos Augusto Fajardo Ariza

“…This device will be based on a Convolutional Neural Network (CNN). We aim to find a suitable CNN model, which later could be implemented in hardware. …”
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The Rapid Detection of Foreign Fibers in Seed Cotton Based on Hyperspectral Band Selection and a Lightweight Neural Network by Yeqi Fei, Zhenye Li, Dongyi Wang, Chao Ni

“…Additionally, a lightweight attention mechanism, combined with a depthwise convolution module, enables real-time inference for online production. …”
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Persian SMS Spam Detection using Machine Learning and Deep Learning Techniques by Roya Khorashadizade, Somayyeh Jafarali Jassbi, Alireza Yari

“…The inconvenience imposed on users, the loss of network traffic, the rise in the calculated cost, occupying more physical space on the mobile phone, and abusing and defrauding recipients are but a few of their downsides. …”
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Methodology to classify high voltage transmission poles using CNN approach from satellite images for safety public regulation application: Study case of rural area in Thailand by Bastien Marty, Raphael Gaudin, Tom Piperno, Didier Rouquette, Cyrille Schwob, Laurent Mezeix

“…Therefore, the use of automatic detection methods enables to facilitate the inspection is necessary to reduce time and cost. Convolutional Neural Network (CNN) is proposed in this work to detect, from Google Earth images, buildings and trees within the safety perimeter of HVTP. …”
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Non-Destructive Measurement of Rice Spikelet Size Based on Panicle Structure Using Deep Learning Method by Ruoling Deng, Weisen Liu, Haitao Liu, Qiang Liu, Jing Zhang, Mingxin Hou

“…The spikelet detection model using convolutional neural network was then established for spikelet recognition and localization. …”
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Hand Gesture Recognition From Wrist-Worn Camera for Human–Machine Interaction by Hong-Quan Nguyen, Trung-Hieu Le, Trung-Kien Tran, Hoang-Nhat Tran, Thanh-Hai Tran, Thi-Lan Le, Hai Vu, Cuong Pham, Thanh Phuong Nguyen, Huu Thanh Nguyen

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