Convolutional Neural Networks for Automatic Identification of Individuals at Terrestrial Terminals by Darwin Yarango-Farro, Alex Mondragon-Fernandez, Heber I. Mejia-Cabrera, Juan Arcila-Diaz

“…The objective of this study was to develop an automated system for the identification of wanted individuals in terrestrial terminals using Convolutional Neural Networks (CNN). The research was conducted under a quantitative approach and a quasi-experimental design. …”
Get full text

A novel hybrid convolutional and transformer network for lymphoma classification by Mohamed Yacin Sikkandar, Sankar Ganesh Sundaram, Muteb Nasser Almeshari, S. Sabarunisha Begum, E. Siva Sankari, Yousef A. Alduraywish, Waeal J. Obidallah, Fahad Mansour Alotaibi

“…This study proposes a hybrid deep learning framework—Hybrid Convolutional and Transformer Network for Lymphoma Classification (HCTN-LC)—designed to enhance the precision and interpretability of lymphoma subtype classification. …”
Get full text

LBT-YOLO: A Lightweight Road Targeting Algorithm Based on Task Aligned Dynamic Detection Heads by Pei Tang, Zhenyu Ding, Minnan Jiang, Weikai Xu, Mao Lv

“…Finally, a new detection head TADDH (Task Aligned Dynamic Detection Head) is proposed. This detection head reduces the number of parameters by sharing the neck network features, and performs task decomposition alignment to achieve high accuracy target detection using dynamic convolution and dynamic feature selection. …”
Get full text

Prediction of crystalline structure evolution during solidification of aluminum at different cooling rates using a hybrid neural network model by Rafi B. Dastagir, Shorup Chanda, Farsia K. Chowdhury, Shahereen Chowdhury, K. Arafat Rahman

Subjects: “…Convolutional neural network…”
Get full text

A root auto tracing and analysis (ARATA): An automatic analysis software for detecting fine roots in images from flatbed optical scanners by Arata Yabuki, Hidetoshi Ikeno, Masako Dannoura

Subjects: “…convolutional neural network…”
Get full text

Associations of greenhouse gases, air pollutants and dynamics of scrub typhus incidence in China: a nationwide time-series study by Haoyue Cao, Jianqiang Han, Weiming Hou, Juxiang Yuan

Get full text

MM-3D Unet: development of a lightweight breast cancer tumor segmentation network utilizing multi-task and depthwise separable convolution by Xian Wang, Wenzhi Zeng, Junzeng Xu, Senhao Zhang, Yuexing Gu, Benhui Li, Xueyang Wang

Subjects: Get full text

RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8 by Lei He, Lei He, Lei He, Dasheng Wu, Dasheng Wu, Dasheng Wu, Xinyu Zheng, Xinyu Zheng, Xinyu Zheng, Fengya Xu, Fengya Xu, Fengya Xu, Shangqin Lin, Shangqin Lin, Shangqin Lin, Siyang Wang, Siyang Wang, Siyang Wang, Fuchuan Ni, Fang Zheng

“…Firstly, it utilizes the large kernel convolution network RepLKNet as the backbone to enhance the extraction of features from targets and complex backgrounds. …”
Get full text

Gas Pipeline Leak Detection by Integrating Dynamic Modeling and Machine Learning Under the Transient State by Juhyun Kim, Sunlee Han, Daehee Kim, Youngsoo Lee

Get full text

Image-data-driven simulation of fluid dynamics (proposal and evaluation) by Nobuto NAKAMICHI, Younghwa CHO, Nobuyuki OSHIMA

Get full text

A Deep Learning Model for NOx Emissions Prediction of a 660 MW Coal-Fired Boiler Considering Multiscale Dynamic Characteristics by Jianrong Huang, Yanlong Ji, Haiquan Yu

Subjects: Get full text

Temporal Relational Graph Convolutional Network Approach to Financial Performance Prediction by Brindha Priyadarshini Jeyaraman, Bing Tian Dai, Yuan Fang

“…Accurately predicting financial entity performance remains a challenge due to the dynamic nature of financial markets and vast unstructured textual data. …”
Get full text

A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

Subjects: Get full text

Lane line detection based on cross-convolutional hybrid attention mechanism by Jianping Wen, Zhuang Zhao, Chenze Wang, Ze Sun, Chao Xu

“…Abstract In order to enhance the accuracy and robustness of lane line recognition in dynamic and complex environments, this paper proposes a lane line detection model based on a cross-convolutional hybrid attention mechanism (CCHA-Net). …”
Get full text

Enhancing Efficiency and Regularization in Convolutional Neural Networks: Strategies for Optimized Dropout by Mehdi Ghayoumi

“…<b>Background/Objectives:</b> Convolutional Neural Networks (CNNs), while effective in tasks such as image classification and language processing, often experience overfitting and inefficient training due to static, structure-agnostic regularization techniques like traditional dropout. …”
Get full text

Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Muhammad Shahzad Sarfraz, Yang Yu, Hafiz Tayyab Rauf

“…To solve this challenge, this paper presents a traffic forecasting model which combines a graph convolutional network, a gated recurrent unit, and a multi-head attention mechanism to simultaneously capture and incorporate the spatio-temporal dependence and dynamic variation in the topological sequence of traffic data effectively. …”
Get full text

Research on sketch instruction recognition technology ased on convolutional neural network by ZHOU Yu, ZHANG Jingtao, LI Ligang, ZHANG Xiaoyan

“…In order to solve the problems of low accuracy of traditional sketch instruction recognition, a sketch instruction recognition technology based on convolutional neural network is proposed. By constructing and optimizing the convolutional neural network model, a large number of sketch instruction samples are used for training, and the accuracy of the validation set is closely monitored throughout the training process, and the learning rate is dynamically adjusted in real time and based on this. …”
Get full text

A point cloud segmentation network with hybrid convolution and differential channels by Xiaoyan Zhang, Yantao Bu

“…Then, we propose a Differential Channel Feature Interaction (DCFI) Module to enhance the local details and global channel information through Differential Convolution (DCU) and a Simplified Channel Attention Mechanism (S_ECA), respectively, and adaptively fuse the two types of information by Dynamic Interaction Mechanism (DIM), achieving their cooperative optimization. …”
Get full text

TOPS-speed complex-valued convolutional accelerator for feature extraction and inference by Yunping Bai, Yifu Xu, Shifan Chen, Xiaotian Zhu, Shuai Wang, Sirui Huang, Yuhang Song, Yixuan Zheng, Zhihui Liu, Sim Tan, Roberto Morandotti, Sai T. Chu, Brent E. Little, David J. Moss, Xingyuan Xu, Kun Xu

“…Here, we report a complex-valued optical convolution accelerator operating at over 2 Tera operations per second (TOPS). …”
Get full text

Rolling Bearing Fault Diagnosis via Temporal-Graph Convolutional Fusion by Fan Li, Yunfeng Li, Dongfeng Wang

“…To address the challenge of incomplete fault feature extraction in rolling bearing fault diagnosis under small-sample conditions, this paper proposes a Temporal-Graph Convolutional Fusion Network (T-GCFN). The method enhances diagnostic robustness through collaborative extraction and dynamic fusion of features from time-domain and frequency-domain branches. …”
Get full text