An efficient network for object detection in scale-imbalanced remote sensing images by Li Zhongyu, Jing Xiaoping, Sun Rui, Yang Yazhi, Wang Wei, Zhu Hongzhen

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New Method of Impact Localization on Plate-like Structures Using Deep Learning and Wavelet Transform by Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

“…This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. …”
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MedFuseNet: fusing local and global deep feature representations with hybrid attention mechanisms for medical image segmentation by Ruiyuan Chen, Saiqi He, Junjie Xie, Tao Wang, Yingying Xu, Jiangxiong Fang, Xiaoming Zhao, Shiqing Zhang, Guoyu Wang, Hongsheng Lu, Zhaohui Yang

“…Although several impressive deep learning architectures based on convolutional neural networks (CNNs) and Transformers have recently demonstrated remarkable performance, there is still potential for further performance improvement due to their inherent limitations in capturing feature correlations of input data. …”
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MSGEGA: Multiscale Gaussian Enhancement and Global-Aware Network for Infrared Small Target Detection by Yuyang Xi, Liuwei Zhang, Ying Jiang, Feng Qian, Fanjiao Tan, Qingyu Hou

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Lightweight Attention-Based CNN Architecture for CSI Feedback of RIS-Assisted MISO Systems by Anming Dong, Yupeng Xue, Sufang Li, Wendong Xu, Jiguo Yu

“…The core contribution of this work lies in an innovative lightweight feedback architecture that deeply integrates multi-layer convolutional neural networks (CNNs) with attention mechanisms. …”
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Deep Attention Networks With Multi-Temporal Information Fusion for Sleep Apnea Detection by Meng Jiao, Changyue Song, Xiaochen Xian, Shihao Yang, Feng Liu

“…This framework utilizes three 1D convolutional neural network (CNN) blocks to extract features from R-R intervals and R-peak amplitudes using segments of varying lengths. …”
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Detection of <i>Helicobacter pylori</i> Infection in Histopathological Gastric Biopsies Using Deep Learning Models by Rafael Parra-Medina, Carlos Zambrano-Betancourt, Sergio Peña-Rojas, Lina Quintero-Ortiz, Maria Victoria Caro, Ivan Romero, Javier Hernan Gil-Gómez, John Jaime Sprockel, Sandra Cancino, Andres Mosquera-Zamudio

“…In this context, deep convolutional neural network (DCNN) models are showing promising results in the automated detection of this infection in whole-slide images (WSIs). …”
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Enhancing maize LAI estimation accuracy using unmanned aerial vehicle remote sensing and deep learning techniques by Zhen Chen, Weiguang Zhai, Qian Cheng

“…Therefore, this study evaluates the potential of multi-source feature fusion and convolutional neural networks (CNN) in estimating maize LAI. …”
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Spectropolarimetric Inversion in Four Dimensions with Deep Learning (SPIn4D). I. Overview, Magnetohydrodynamic Modeling, and Stokes Profile Synthesis by Kai E. Yang, Lucas A. Tarr, Matthias Rempel, S. Curt Dodds, Sarah A. Jaeggli, Peter Sadowski, Thomas A. Schad, Ian Cunnyngham, Jiayi Liu, Yannik Glaser, Xudong Sun

“…Here, we provide an overview of our “SPIn4D” project, which aims to develop deep convolutional neural networks (CNNs) for estimating the physical properties of the solar photosphere from DKIST spectropolarimetric observations. …”
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Comparative Analysis of Vision Transformers and CNN Models for Driver Fatigue Classification by Fadhlan Hafizhelmi Kamaru Zaman, Kok Mun Ng, Syahrul Afzal Che Abdullah

“… This study provides a comprehensive evaluation of Convolutional Neural Network (CNN) and Vision Transformer (ViT) models for driver fatigue classification, a critical issue in road safety. …”
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Explainable clinical diagnosis through unexploited yet optimized fine-tuned ConvNeXt Models for accurate monkeypox disease classification by Muhammad Waqar, Zeshan Aslam Khan, Shanzey Tariq Khawaja, Naveed Ishtiaq Chaudhary, Saadia Khan, Khalid Mehmood Cheema, Muhammad Farhan Khan, Syed Sohail Ahmed, Muhammad Asif Zahoor Raja

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A bird song detector for improving bird identification through deep learning: A case study from Doñana by Alba Márquez-Rodríguez, Miguel Ángel Mohedano-Munoz, Manuel J. Marín-Jiménez, Eduardo Santamaría-García, Giulia Bastianelli, Pedro Jordano, Irene Mendoza

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DCCPNet: A Dual-Branch Channel Cross-Concatenation Pan-Sharpening Network for Satellite Remote Sensing Imagery by Zechun Li, Xunqiang Gong, Ailong Ma, Haiqing He, Pengyuan Lv, Xiansan Liu, Yanfei Zhong

“…Within this framework, hierarchical features are extracted through multiscale convolution residual (MCR) blocks, while complementary spatial and spectral information is adaptively fused in the DCC blocks. …”
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Optimizing Fingerprint Identification: CNNs With Raw Images Versus Handcrafted Features for Real-Time Systems by Shaik Salma, Tauheed Ahmed, Garimella Ramamurthy

“…Despite progress, existing systems still face challenges with noise, database differences, and real-time speed. This study investigates the balance between accuracy and computational efficiency(thereby speed) by comparing two approaches: training a Convolutional Neural Network (CNN) with raw fingerprint images and training a CNN using handcrafted fingerprint features. …”
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Text analysis of DNS queries for data exfiltration protection of computer networks by Ya. V. Bubnov, N. N. Ivanov

“…The paper proposes a method of detecting such DNS requests based on text classification of domain names by convolutional neural network. The efficiency of the method is based on assumption that domain names exploited for data exfiltration differ from domain names formed from words of natural language. …”
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Development of low-cost portable spectrometer equipped with 18-band spectral sensors using deep learning model for evaluating moisture content of rubber sheets by Amorndej Puttipipatkajorn, Amornrit Puttipipatkajorn

“…During testing of the instrument, the results indicated that its predictive performance did not differ significantly from that of the primary calibration model. …”
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Metric learning unveiling disparities: A novel approach to recognize false trigger images in wildlife monitoring by Rui Zhu, Enting Zhao, Chunhe Hu, Jiangjian Xie, Junguo Zhang, Huijian Hu

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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

“…This review examines the development and performance of DL architectures, notably convolutional neural networks (CNNs) and emerging vision transformers (ViTs), in identifying COVID-19-related lung abnormalities. …”
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Enhanced Osteoporosis Detection Using Artificial Intelligence: A Deep Learning Approach to Panoramic Radiographs with an Emphasis on the Mental Foramen by Robert Gaudin, Wolfram Otto, Iman Ghanad, Stephan Kewenig, Carsten Rendenbach, Vasilios Alevizakos, Pascal Grün, Florian Kofler, Max Heiland, Constantin von See

“…A pretrained convolutional neural network (CNN) classifier was used for training, testing, and validation with a random split of the dataset into subsets (A vs. …”
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Automatic Detection and Calculation of Mining Subsidence in Large-Scale Interferograms With Transformer-CNN Model by Hongdong Fan, Jialin Xin, Tao Lin, Jun Wang

“…Subsequently, the Residual Convolution Block and Swin Transformer Block were adopted as the fundamental building blocks of the model architecture to develop RAUNet, a synergistic network designed for detecting and calculating wide-area mining subsidence zones. …”
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