IEEE

Brain Cancer MRI Classification using CNN Architectures with Grid Search Enhanced with Coordinate Ascent Optimization

Abstract: Magnetic resonance imaging (MRI) is an important tool for brain cancer diagnosis and classification. Combined with modern convolutional neural network (CNN) technology, it can effectively ...
IEEE

Brightness-Enhanced Gastrointestinal Endoscopy Image Classification Using CNN-Based Diagnostic Model

Abstract: This study proposes a framework based on a Cycle-Consistent Generative Adversarial Network (CycleGAN) to improve the image brightness and visual continuity of gastrointestinal (GI) ...
IEEE

AI-Powered Intelligent Crop Health Monitoring System using CNN-based Image Classification

Abstract: Plant and leaf diseases have a significant impact on agricultural production, leading to a decrease in crop yield and quality. Effective crop management demands early and precise detection ...
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

Effectiveness of K-means Clustering-Based Outlier Handling Techniques in Colonic Condition Endoscopy Image Classification Using CNN

Abstract: Colorectal cancer is one of the leading causes of cancer death worldwide, so accurate early detection is needed. Endoscopic imaging technology plays a vital role in diagnosis, but the ...
IEEE

S2CaT: Spatial-Spectral-based CNN and Transformer Network for Hyperspectral Image Classification

Abstract: Recent advancements in the field of hyperspectral image (HSI) analysis have highlighted the potential of hybrid architectures that integrate convolutional neural networks (CNNs) with ...
IEEE

Enhancing Lung Cancer Classification Using CNN and SVM Methods

As one of the most common and deadly types of cancer in the world, lung cancer continues to pose a serious threat to both healthcare systems and researchers. The prognosis of lung cancer patients ...
IEEE

Deep Learning for Lung Cancer Classification: An Optimized 2D CNN Approach for CT Image Recognition

Abstract: This research work presents a deep learning method using the Convolutional Neural Network (CNN) for automated lung image classification based on Computer Tomography (CT) scan datasets. The ...
IEEE

Cross-Domain Hyperspectral Image Classification via Mamba–CNN and Knowledge Distillation

Abstract: Domain adaptation (DA)-based cross-domain hyperspectral image (HSI) classification methods have garnered significant attention. The majority of DA techniques utilize models based on ...