IEEE

Cross-Scale Window Attention for Cross-Domain Hyperspectral Image Classification

Abstract: Hyperspectral image classification (HSIC) is crucial in several fields, but relies on a large number of labeled samples. Due to the high cost of manual annotation and the scarcity of samples ...
IEEE

Asymmetric Mamba–CNN Collaborative Architecture for Large-Size Remote Sensing Image Semantic Segmentation

Large-size remote sensing images contain rich geographical information. Efficient and accurate semantic segmentation of these images is of significant importance in various fields. However, the ...
IEEE

CNN-Based Plant Disease Classification: An Image Analysis Approach

Abstract: The agriculture industry faces significant challenges in maintaining sustainable plant growth while combating diseases that threaten crops. Traditional disease prevention methods rely on ...
IEEE

A Verilog based Approach for Object Detection using CNN

Abstract: A Convolutional Neural Network (CNN) are a class of artificial neural networks specifically designed to process data with a grid-like topology, such as images, making them well-suited for ...
IEEE

Bone Fracture Classification Using Deep Learning Models with Transfer Learning

Abstract: Bone fracture can be defined as the complete or partial disruption of the integrity of bone tissue. Early and accurate diagnosis of fractures plays a decisive role in the effectiveness of ...
IEEE

Remote Sensing Scene Image Classification with Swin Transformer-Based Transfer Learning

Abstract: In remote sensing classification problems, high visual similarity between scenes reduces the classification performance of traditional methods. Therefore, advanced deep neural network models ...
IEEE

Probabilistic Forecasting for Battery Health Estimation Using CNN-LSTM on Augmented Multi-Operation Data

Abstract: Ensuring the safety and reliability of electric vehicles and energy storage systems requires an effective evaluation of lithium-ion battery State of Health (SOH). Most current methods are ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

Deep Learning for Skin Cancer Detection: Multi-Class Lesion Classification Using CNN Architecture

Abstract: Skin cancer ranks among ubiquitous malignancies, its prevalence escalating due to ecological shifts and protracted ultraviolet (UV)exposure. This study aims to address the pressing need for ...
IEEE

Custom Dataset-Driven Unsupervised Low-Light Image Enhancement Using 2D CNN

Abstract: Low-light image augmentation, which seeks to improve image visibility and quality under low illumination, is an important job in computer vision. We investigate underexposure image ...
IEEE

Enhancing GNSS Localization in Urban Canyons With a Hybrid CNN-Autoencoder Approach to LOS/NLOS Classification

Abstract: Non-Line-of-Sight (NLOS) reception is acknowledged as a primary source of positioning error in Global Navigation Satellite System (GNSS) applications ...
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) ...