Convolutional Neural Network
Convolutional Neural Networks (CNNs) are a class of deep learning models designed for processing grid-like data, excelling in image analysis and related tasks. Current research focuses on improving CNN efficiency and robustness, exploring architectures like EfficientNet and Swin Transformers, as well as novel approaches such as Mamba models to address limitations in computational cost and long-range dependency capture. This active field of research has significant implications across diverse applications, including medical image analysis (e.g., cancer detection, Alzheimer's diagnosis), damage assessment, and art forgery detection, demonstrating the power of CNNs for automating complex visual tasks.
Papers
High-Resolution Detection of Earth Structural Heterogeneities from Seismic Amplitudes using Convolutional Neural Networks with Attention layers
Luiz Schirmer, Guilherme Schardong, Vinícius da Silva, Rogério Santos, Hélio Lopes
Hyperspectral Reconstruction of Skin Through Fusion of Scattering Transform Features
Wojciech Czaja, Jeremiah Emidih, Brandon Kolstoe, Richard G. Spencer
RandAlign: A Parameter-Free Method for Regularizing Graph Convolutional Networks
Haimin Zhang, Min Xu
Privacy-Preserving Intrusion Detection using Convolutional Neural Networks
Martin Kodys, Zhongmin Dai, Vrizlynn L. L. Thing
Hybrid FedGraph: An efficient hybrid federated learning algorithm using graph convolutional neural network
Jaeyeon Jang, Diego Klabjan, Veena Mendiratta, Fanfei Meng
Advanced wood species identification based on multiple anatomical sections and using deep feature transfer and fusion
Kallil M. Zielinski, Leonardo Scabini, Lucas C. Ribas, Núbia R. da Silva, Hans Beeckman, Jan Verwaeren, Odemir M. Bruno, Bernard De Baets
On Input Formats for Radar Micro-Doppler Signature Processing by Convolutional Neural Networks
Mikolaj Czerkawski, Carmine Clemente, Craig Michie, Christos Tachtatzis
Convolutional neural network classification of cancer cytopathology images: taking breast cancer as an example
MingXuan Xiao, Yufeng Li, Xu Yan, Min Gao, Weimin Wang
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network
Mayura Manawadu, Udaya Wijenayake
Edge-Efficient Deep Learning Models for Automatic Modulation Classification: A Performance Analysis
Nayan Moni Baishya, B. R. Manoj, Prabin K. Bora
Improving Shift Invariance in Convolutional Neural Networks with Translation Invariant Polyphase Sampling
Sourajit Saha, Tejas Gokhale
Toward a Better Understanding of Fourier Neural Operators from a Spectral Perspective
Shaoxiang Qin, Fuyuan Lyu, Wenhui Peng, Dingyang Geng, Ju Wang, Xing Tang, Sylvie Leroyer, Naiping Gao, Xue Liu, Liangzhu Leon Wang
Driver Attention Tracking and Analysis
Dat Viet Thanh Nguyen, Anh Tran, Hoai Nam Vu, Cuong Pham, Minh Hoai
An Animation-based Augmentation Approach for Action Recognition from Discontinuous Video
Xingyu Song, Zhan Li, Shi Chen, Xin-Qiang Cai, Kazuyuki Demachi