IEEE

Explainable Brain Tumor Classification using CNN and GradCAM

Abstract: One of the most critical neurological conditions is Brain tumors, timely and correct diagnosis is needed for effective treatment. Advances in neuroimaging technology such as MRI, limitations ...
IEEE

Multilevel Multimodal CNN–Transformer Fusion Network for Land Use and Land Cover Classification

Abstract: In remote sensing (RS), convolutional neural networks (CNNs) are well-recognized for their spatial–spectral feature extraction capabilities, whereas vision transformers (ViTs), which ...
IEEE

A Deep Learning Approach Based on XAI and ViT-GRU Hybrid Model for Brain Tumor Classification Using MRI Images

Abstract: Brain tumors (BT), resulting from uncontrolled cell proliferation in the central nervous system, present significant diagnostic challenges due to their anatomical complexity and interpatient ...
IEEE

AI-Driven Emerging Trends, Challenges, and Future Directions for Brain Tumor Detection in Healthcare

Abstract: Brain tumors are among the most serious health conditions, requiring early and accurate diagnosis to improve patient outcomes. This review analyzes a wide range of artificial intelligence ...
IEEE

A Two-Stage YOLO-CNN Framework for Automated Lithium-ion Battery Defect Inspection

Abstract: Lithium-ion batteries (LIBs) are widely used in electric vehicles and energy storage systems, but their inspection remains a challenge. Manual visual inspection is labor-intensive, ...
WRAL

First on CNN: Noninvasive brain treatment for depression proves helpful

CNN — (CNN) — Summer passed Valerie Zeko by when she was 27, as she vegged out on the couch watching TV instead of seeing friends or exploring the overcast beach near her house. She later learned that ...
IEEE

Computer-Aided Classification of Skin Cancer based on the YOLO Algorithm

Abstract: Skin cancer is considered to be the most common type of cancer worldwide. Nonetheless, the corresponding death rate can be considerably reduced with early detection and classification.
IEEE

A Multimodal Adaptive Inter-Region Attention-Guided Network for Brain Tumor Classification

Abstract: Accurate brain tumor classification is critical for ensuring timely and effective medical interventions. In recent years, artificial intelligence (AI)-driven diagnostic systems have emerged ...
IEEE

Explainable Brain Tumor Classification Using Grad-CAM and a Transfer Learning Approach

Abstract: The complex structure and indistinguishable visual differences of brain tumors poses a significant challenge in medical diagnostics. This study presents a novel deep-learning based approach ...
IEEE

Transformer-Driven Offset Convolutional Network for Brain Tumor MRI Classification

Abstract: Although brain tumors can be diagnosed using magnetic resonance imaging (MRI), automatic classification remains challenging due to the complex and irregular shapes of tumors. This paper ...
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

Implementation of Brain Tumor Detection and Classification Model Using CNN Approach

Abstract: Unless diagnosed and treated early, brain tumors unusual growths may prove to be lethal. Even with the standard methods, such as MRI scans, to precisely diagnose brain cancers, it may be ...