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
SiamQuality: A ConvNet-Based Foundation Model for Imperfect Physiological Signals
Cheng Ding, Zhicheng Guo, Zhaoliang Chen, Randall J Lee, Cynthia Rudin, Xiao Hu
ChangeBind: A Hybrid Change Encoder for Remote Sensing Change Detection
Mubashir Noman, Mustansar Fiaz, Hisham Cholakkal
Spatial-frequency Dual-Domain Feature Fusion Network for Low-Light Remote Sensing Image Enhancement
Zishu Yao, Guodong Fan, Jinfu Fan, Min Gan, C.L. Philip Chen
LM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks
Vanesa Gómez-Martínez, Francisco J. Lara-Abelenda, Pablo Peiro-Corbacho, David Chushig-Muzo, Conceicao Granja, Cristina Soguero-Ruiz
Road Surface Friction Estimation for Winter Conditions Utilising General Visual Features
Risto Ojala, Eerik Alamikkotervo
Research on geometric figure classification algorithm based on Deep Learning
Ruiyang Wang, Haonan Wang, Junfeng Sun, Mingjia Zhao, Meng Liu
Application of Long-Short Term Memory and Convolutional Neural Networks for Real-Time Bridge Scour Prediction
Tahrima Hashem, Negin Yousefpour
Perception and Localization of Macular Degeneration Applying Convolutional Neural Network, ResNet and Grad-CAM
Tahmim Hossain, Sagor Chandro Bakchy
OpTC -- A Toolchain for Deployment of Neural Networks on AURIX TC3xx Microcontrollers
Christian Heidorn, Frank Hannig, Dominik Riedelbauch, Christoph Strohmeyer, Jürgen Teich
Vision Transformer-based Adversarial Domain Adaptation
Yahan Li, Yuan Wu
CFPFormer: Feature-pyramid like Transformer Decoder for Segmentation and Detection
Hongyi Cai, Mohammad Mahdinur Rahman, Jingyu Wu, Yulun Deng
DP-Net: Learning Discriminative Parts for image recognition
Ronan Sicre, Hanwei Zhang, Julien Dejasmin, Chiheb Daaloul, Stéphane Ayache, Thierry Artières
A Learning Paradigm for Interpretable Gradients
Felipe Torres Figueroa, Hanwei Zhang, Ronan Sicre, Yannis Avrithis, Stephane Ayache
CNN2GNN: How to Bridge CNN with GNN
Ziheng Jiao, Hongyuan Zhang, Xuelong Li
SC-HVPPNet: Spatial and Channel Hybrid-Attention Video Post-Processing Network with CNN and Transformer
Tong Zhang, Wenxue Cui, Shaohui Liu, Feng Jiang