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
Raw Audio Classification with Cosine Convolutional Neural Network (CosCovNN)
Kazi Nazmul Haque, Rajib Rana, Tasnim Jarin, Bjorn W. Schuller Jr
HSLiNets: Hyperspectral Image and LiDAR Data Fusion Using Efficient Dual Linear Feature Learning Networks
Judy X Yang, Jing Wang, Chen Hong Sui, Zekun Long, Jun Zhou
SS Linear Fusion Model: Hyperspectral Imaging Efficient Spatial and Spectral Linear Model with Bidirectional Feature Learning
Judy X Yang, Jing Wang, Zekun Long, Chenhong Sui, Jun Zhou
Twisted Convolutional Networks (TCNs): Enhancing Feature Interactions for Non-Spatial Data Classification
Junbo Jacob Lian
LDA-AQU: Adaptive Query-guided Upsampling via Local Deformable Attention
Zewen Du, Zhenjiang Hu, Guiyu Zhao, Ying Jin, Hongbin Ma
A Simple Sparse Matrix Vector Multiplication Approach to Padded Convolution
Zan Chaudhry
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data
Aoran Shen, Minghao Dai, Jiacheng Hu, Yingbin Liang, Shiru Wang, Junliang Du
Pruning Deep Convolutional Neural Network Using Conditional Mutual Information
Tien Vu-Van, Dat Du Thanh, Nguyen Ho, Mai Vu
Preserving Information: How does Topological Data Analysis improve Neural Network performance?
A. Stolarek, W. Jaworek
Convolutional Neural Networks Do Work with Pre-Defined Filters
Christoph Linse, Erhardt Barth, Thomas Martinetz
Real-time Video Target Tracking Algorithm Utilizing Convolutional Neural Networks (CNN)
Chaoyi Tan, Xiangtian Li, Xiaobo Wang, Zhen Qi, Ao Xiang
KANs for Computer Vision: An Experimental Study
Karthik Mohan, Hanxiao Wang, Xiatian Zhu
Breast Tumor Classification Using EfficientNet Deep Learning Model
Majid Behzadpour, Bengie L. Ortiz, Ebrahim Azizi, Kai Wu
Rapid Deployment of Domain-specific Hyperspectral Image Processors with Application to Autonomous Driving
Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe, Óscar Mata-Carballeira, M. Victoria Martínez
Deep Convolutional Neural Networks Structured Pruning via Gravity Regularization
Abdesselam Ferdi
Path Loss Prediction Using Deep Learning
Ryan Dempsey, Jonathan Ethier, Halim Yanikomeroglu
Low-Data Classification of Historical Music Manuscripts: A Few-Shot Learning Approach
Elona Shatri, Daniel Raymond, George Fazekas