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

Hyperspectral Image Classification via Cross-Domain Few-Shot Learning With Multilevel Style and Semantic Enhancement

Abstract: One of the key challenges in cross-domain few-shot hyperspectral image classification (HSIC) lies in effectively leveraging spectral-spatial features while alleviating semantic ...
IEEE

A Multiple Backbone Feature Fusion Ensemble CNN for Brain Tumor Detection and Classification from MRI Images

Abstract: Accurate classification of brain tumors from magnetic resonance imaging (MRI) scans is essential for early diagnosis and reliable clinical decision-making. However, variations in tumor ...
IEEE

Uncertainty-Aware Local Bayesian Framework for Hyperspectral Image Classification With Noisy Labels

Abstract: Various deep learning-based methods have greatly improved hyperspectral image (HSI) classification performance, but these models are sensitive to noisy training labels. Human annotation on ...
IEEE

MATCNN: Infrared and Visible Image Fusion Method Based on Multiscale CNN With Attention Transformer

Abstract: While attention-based approaches have shown considerable progress in enhancing image fusion and addressing the challenges posed by long-range feature dependencies, their efficacy in ...
IEEE

Region-Relation Enhanced GNN-CNN for Image Classification

Abstract: Convolutional Neural Networks (CNNs) excel in local feature extraction but struggle to model regional semantic correlations and global context. This paper proposes a GNNintegrated framework ...
IEEE

CNNGP: Multi-tree Genetic Programming Integrating Pre-trained CNN Features for Fine-Grained Image Classification

Abstract: Fine-grained image classification (FGIC) remains a challenging task due to subtle inter-class differences and significant intra-class variations, particularly under limited training data.
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

Rice Leaf Diseases Classification Using CNN with Transfer Learning

Abstract: In the field of agriculture, plant diseases pose a serious threat to achieving optimal yields and food security; thus, identifying and classifying rice leaf diseases correctly are key points ...
IEEE

Deep Learning-Driven Image Classification of Jellyfish: A CNN Model Approach

Abstract: Rising in importance as an environmental problem, jellyfish blooms impair aquaculture infrastructure, upset marine ecosystems, and reveal human health risks. Good early reaction and ...
IEEE

MCBL-UNet: A Hybrid Mamba-CNN Boundary Enhanced Light-weight UNet for Placenta Ultrasound Image Segmentation

Abstract: The shape and size of the placenta are closely related to fetal development in the second and third trimesters of pregnancy. Accurately segmenting the placental contour in ultrasound images ...
IEEE

Deep Learning-Based Mushroom Species Classification: Analyzing the Performance of CNN on Diverse Fungi

Abstract: This paper proposes the classification of mushrooms using the EfficientNetB7 deep learning architecture. Correct classification of mushrooms is important because most species are considered ...