Deep Convolutional Neural Network

Deep convolutional neural networks (CNNs) are a class of artificial neural networks designed to process data with a grid-like topology, such as images and videos, excelling at tasks like image classification, object detection, and segmentation. Current research focuses on improving CNN architectures (e.g., exploring variations of ResNet, Inception, and efficientNet models), developing novel training techniques (like integer-only training and self-knowledge distillation), and addressing challenges such as imbalanced datasets and catastrophic forgetting in incremental learning. The widespread application of CNNs across diverse fields, from medical image analysis and autonomous driving to agricultural monitoring and remote sensing, highlights their significant impact on both scientific understanding and practical problem-solving.

Papers

November 7, 2024

EffiCANet: Efficient Time Series Forecasting with Convolutional Attention
Xinxing Zhou, Jiaqi Ye, Shubao Zhao, Ming Jin, Chengyi Yang, Yanlong Wen, Xiaojie Yuan
Deep Convolutional Neural Network Human Attention Group Convolution Large Kernel Convolution Superior Forecasting Efficient Time Series Forecasting

November 4, 2024

GraphVL: Graph-Enhanced Semantic Modeling via Vision-Language Models for Generalized Class Discovery
Bhupendra Solanki, Ashwin Nair, Mainak Singha, Souradeep Mukhopadhyay, Ankit Jha, Biplab Banerjee
Vision Language Model Deep Convolutional Neural Network Vision Language Contrastive Loss Generalized Category Discovery Semantic Model Contextual Response Retrievability Loss Function

November 3, 2024

November 2, 2024

Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement
Bryan Bo Cao, Lawrence O'Gorman, Michael Coss, Shubham Jain
New Benchmark Deep Convolutional Neural Network Supervised ImageNet Vision Model Selection Policy Multi Class Shot Class Data Complexity

November 1, 2024

Inducing Semi-Structured Sparsity by Masking for Efficient Model Inference in Convolutional Networks
David A. Danhofer
Convolutional Neural Network Deep Convolutional Neural Network Scientific Inference Structured Sparsity Convolution Kernel Efficient Model Sparsity Pattern

October 31, 2024

October 29, 2024

October 26, 2024

CAVE: Classifying Abnormalities in Video Capsule Endoscopy
Ishita Harish, Saurav Mishra, Neha Bhadoria, Rithik Kumar, Madhav Arora, Syed Rameem Zahra, Ankur Gupta
Deep Neural Network Deep Convolutional Neural Network Virtual Environment Ensemble Based Capsule Endoscopy Evident Abnormality

October 23, 2024

Real time anomalies detection on video
Fabien Poirier
Data Detection Deep Convolutional Neural Network Real Time LSTM Network Source Video Deep Learning Approach Surveillance Camera Video Snapshot

October 22, 2024

Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features
Christoph Linse, Beatrice Brückner, Thomas Martinetz
Convolutional Neural Network Deep Convolutional Neural Network CNN Model Extreme Edge Convolution Layer Traditional Convolutional Enhancing Generalization Line Feature Novel Regularization

October 21, 2024

October 18, 2024

Learning to Control the Smoothness of Graph Convolutional Network Features
Shih-Hsin Wang, Justin Baker, Cory Hauck, Bao Wang
Deep Convolutional Neural Network Node Classification Feature Wise Graph Convolutional Network Convolutional Layer Average Smoothness

Deep Convolutional Neural Network

Papers

EffiCANet: Efficient Time Series Forecasting with Convolutional Attention

GraphVL: Graph-Enhanced Semantic Modeling via Vision-Language Models for Generalized Class Discovery

Flexible Coded Distributed Convolution Computing for Enhanced Fault Tolerance and Numerical Stability in Distributed CNNs

Chronic Obstructive Pulmonary Disease Prediction Using Deep Convolutional Network

Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement

Inducing Semi-Structured Sparsity by Masking for Efficient Model Inference in Convolutional Networks

Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia

Deep Convolutional Neural Networks on Multiclass Classification of Three-Dimensional Brain Images for Parkinson's Disease Stage Prediction

Enhanced Survival Prediction in Head and Neck Cancer Using Convolutional Block Attention and Multimodal Data Fusion

On filter design in deep convolutional neural network

Empirical curvelet based Fully Convolutional Network for supervised texture image segmentation

Audio Classification of Low Feature Spectrograms Utilizing Convolutional Neural Networks

Interpretable Image Classification with Adaptive Prototype-based Vision Transformers

CAVE: Classifying Abnormalities in Video Capsule Endoscopy

Real time anomalies detection on video

Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line Features

Training Better Deep Learning Models Using Human Saliency

An Explainable Contrastive-based Dilated Convolutional Network with Transformer for Pediatric Pneumonia Detection

Hybrid Architecture for Real-Time Video Anomaly Detection: Integrating Spatial and Temporal Analysis

Learning to Control the Smoothness of Graph Convolutional Network Features