IEEE

Improving GNNs for Image Classification: Addressing Homophily Challenges

Abstract: Graph Neural Networks (GNNs) are rapidly becoming essential tools in deep learning, but their effectiveness when applied to images is often limited by challenges in graph representation.
IEEE

Novel Mask R-CNN Based Mushroom Cluster Tracking in Time-Lapse Images From a Farm Environment

Abstract: This study aims to develop a novel deep learningbased approach to support the automated mushroom growth monitoring using an object tracking algorithm in conjunction with instance ...
Scientific Research Publishing

A Lightweight MobileViT with a Dual-Path Attention Mechanism for MRI Image Classification ()

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...
IEEE

CNN-Based Image Forgery Detection Using Sequential Deep Learning Architecture

Abstract: The wide availability of digital image editing tools and software has made it highly straightforward to tamper with or modify digital media or photographic evidence, which shows that it is ...
IEEE

Hybrid CNN-Transformer Model for Accurate Classification of Human Attention Levels Using Workplace EEG Data

Abstract: Accurately detecting human attention levels is a key challenge in cognitive neuroscience, with broad application value in improving productivity. Although Electroencephalography (EEG) ...
IEEE

Few-Shot Learning Based on Multilevel Contrast for Cross-Domain Hyperspectral Image Classification

Abstract: Recently, domain adaptation techniques have been introduced for cross-domain few-shot hyperspectral image (HSI) classification tasks, but effectively aligning the source and target domains ...
IEEE

Feature Distribution-Based Touch Biometrics Using CNN and Siamese Networks

Abstract: Ensuring secure and user-friendly authentication is important as mobile devices increasingly handle sensitive data. Traditional methods like PINs, fingerprints, and facial recognition have ...
IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
IEEE

UAV Image Classification: A Comparative Evaluation of CNN Models

Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...
KOAM News Now

Mississippi senator to face a prosecutor she blocked from the federal bench, CNN projects

(CNN) — Mississippi’s Senate primaries set up a general election showdown between an incumbent and a challenger she blocked from federal judgeship. CNN projected Tuesday that Republican Sen. Cindy ...
IEEE

DL-Clean: CNN-Based Waste Classification for Smart City Infrastructure

Abstract: Automated waste sorting is a tedious and, more importantly, an error-prone task. This study attempts to channel the potential of CNNs in fighting pollution to the automation of waste sorting ...
IEEE

Automatic classification of Household waste using deep learning

Abstract: Waste sorting serves as a highly effective approach to reduce waste at the source and promote resource recycling. It can significantly decrease the amount of waste needing final disposal ...