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
Squeeze-and-Remember Block
Rinor Cakaj, Jens Mehnert, Bin Yang
Simplified priors for Object-Centric Learning
Vihang Patil, Andreas Radler, Daniel Klotz, Sepp Hochreiter
On the Geometry and Optimization of Polynomial Convolutional Networks
Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn
Interactive Explainable Anomaly Detection for Industrial Settings
Daniel Gramelt, Timon Höfer, Ute Schmid
KPCA-CAM: Visual Explainability of Deep Computer Vision Models using Kernel PCA
Sachin Karmani, Thanushon Sivakaran, Gaurav Prasad, Mehmet Ali, Wenbo Yang, Sheyang Tang
Cartesian Genetic Programming Approach for Designing Convolutional Neural Networks
Maciej Krzywda, Szymon Łukasik, Amir Gandomi H
A Hierarchical conv-LSTM and LLM Integrated Model for Holistic Stock Forecasting
Arya Chakraborty, Auhona Basu
Leveraging CAM Algorithms for Explaining Medical Semantic Segmentation
Tillmann Rheude, Andreas Wirtz, Arjan Kuijper, Stefan Wesarg
Adaptive high-precision sound source localization at low frequencies based on convolutional neural network
Wenbo Ma, Yan Lu, Yijun Liu
Learning Partial Differential Equations with Deep Parallel Neural Operators
Qinglong Ma, Peizhi Zhao, Sen Wang, Tao Song
A Self-attention Residual Convolutional Neural Network for Health Condition Classification of Cow Teat Images
Minghao Wang
CCDepth: A Lightweight Self-supervised Depth Estimation Network with Enhanced Interpretability
Xi Zhang, Yaru Xue, Shaocheng Jia, Xin Pei
SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory Spatial Attention Decoding
Ziyang Zhang, Andrew Thwaites, Alexandra Woolgar, Brian Moore, Chao Zhang
Spectral Wavelet Dropout: Regularization in the Wavelet Domain
Rinor Cakaj, Jens Mehnert, Bin Yang
Early diagnosis of Alzheimer's disease from MRI images with deep learning model
Sajjad Aghasi Javid, Mahmood Mohassel Feghhi
Enhanced Convolution Neural Network with Optimized Pooling and Hyperparameter Tuning for Network Intrusion Detection
Ayush Kumar Sharma, Sourav Patel, Supriya Bharat Wakchaure, Abirami S
Med-IC: Fusing a Single Layer Involution with Convolutions for Enhanced Medical Image Classification and Segmentation
Md. Farhadul Islam, Sarah Zabeen, Meem Arafat Manab, Mohammad Rakibul Hasan Mahin, Joyanta Jyoti Mondal, Md. Tanzim Reza, Md Zahidul Hasan, Munima Haque, Farig Sadeque, Jannatun Noor