Different Convolutional Neural Network

Convolutional Neural Networks (CNNs) are a cornerstone of modern computer vision, used extensively for image and video analysis across diverse applications. Current research focuses on optimizing CNN architectures for specific tasks, exploring variations like lightweight networks for resource-constrained devices, and comparing the performance of established models (e.g., ResNet, DenseNet, MobileNet, VGG) with newer architectures and techniques such as Transformers. This research is crucial for advancing fields ranging from medical image analysis and precision agriculture to industrial automation and environmental monitoring, driving improvements in accuracy, efficiency, and applicability of CNN-based solutions.

Papers

April 11, 2022

Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study
Pouya Moeinifard, Mohammad Sadra Rajabi, Maryam Bitaraf
Convolutional Neural Network Case Study Convolutional Neural Network Model Structural Health Monitoring Different Convolutional Neural Network Vibration Data

April 2, 2022

AdaSmooth: An Adaptive Learning Rate Method based on Effective Ratio
Jun Lu
Gradient Descent Multi Layer Learning Rate Stochastic Optimization Different Convolutional Neural Network

March 4, 2022

Exploration of Various Deep Learning Models for Increased Accuracy in Automatic Polyp Detection
Ariel E. Isidro, Arnel C. Fajardo, Alexander A. Hernandez
Deep Learning Deep Learning Model Transfer Learning Environment Exploration Accuracy Improvement Polyp Detection Different Convolutional Neural Network Colonoscopy Image

January 23, 2022

Deeply Explain CNN via Hierarchical Decomposition
Ming-Ming Cheng, Peng-Tao Jiang, Ling-Hao Han, Liang Wang, Philip Torr
CNN Model Part Whole Hierarchy Different Convolutional Neural Network Hierarchical Decomposition Gradient Propagation

January 10, 2022

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks
Claudio Filipi Gonçalves dos Santos, João Paulo Papa
Convolutional Neural Network Timely Survey Data Augmentation Regularization Model Model Overfitting Regularization Technique Different Convolutional Neural Network Regularization Approach

January 9, 2022

ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
Rui-Yang Ju, Ting-Yu Lin, Jia-Hao Jian, Jen-Shiun Chiang, Wei-Bin Yang
Model Compression Neural Network Architecture New Connection SE SPP DenseNet Different Convolutional Neural Network EfficientNet Algorithm Efficient CNN

December 20, 2021

Driver Drowsiness Detection Using Ensemble Convolutional Neural Networks on YawDD
Rais Mohammad Salman, Mahbubur Rashid, Rupal Roy, Md Manjurul Ahsan, Zahed Siddique
Convolutional Neural Network Different Convolutional Neural Network Drowsiness Detection Driver Drowsiness Detection Driver Drowsiness

December 15, 2021

An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network
Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus Zaharia
Convolutional Neural Network Deep Neural Network Global Impact Supervised ImageNet Edge Pruning Pruning Method Experimental Study Different Convolutional Neural Network Pruning Strategy

November 16, 2021

Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset
Mina Bishay, Ahmed Ghoneim, Mohamed Ashraf, Mohammad Mavadati
Convolutional Neural Network Study Feature Large Scale Dataset Different Convolutional Neural Network Action Unit Detection Large Scale Naturalistic Training Environment

Different Convolutional Neural Network

Papers

Lost Vibration Test Data Recovery Using Convolutional Neural Network: A Case Study

AdaSmooth: An Adaptive Learning Rate Method based on Effective Ratio

Exploration of Various Deep Learning Models for Increased Accuracy in Automatic Polyp Detection

Deeply Explain CNN via Hierarchical Decomposition

Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks

ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections

Driver Drowsiness Detection Using Ensemble Convolutional Neural Networks on YawDD

An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network

Which CNNs and Training Settings to Choose for Action Unit Detection? A Study Based on a Large-Scale Dataset