IEEE

Robotic Automation Dynamic Hybrid Neuro-Fuzzy and Deep Learning Framework with GRU-BiLSTM, Capsule Networks, Type-2 Fuzzy Logic and CNN-TCN for Accurate IoMT-Based Chronic ...

Abstract: Background Information: Chronic kidney disease (CKD) is a world health concern that requires an early detection and careful observation over time. The IoMT is offering continuously streaming ...
IEEE

Leveraging Deep Learning for Accurate Classification of Wild Mushrooms: A Hybrid ResNet and Region-Based CNN Approach

Abstract: Accurate mushroom classification is essential for applications ranging from ecological research to foraging safety. This study proposes a convolutional neural network (CNN) based approach ...
IEEE

Deep Learning for Handwritten Hindi Character Recognition: A CNN-Based Implementation

Abstract: This manuscript delineates a sophisticated framework for the recognition of handwritten Hindi characters, employing diverse deep learning methodologies. Within this study, we proffer a ...
IEEE

Improving Alzheimer’s Diagnosis with Deep Learning and Pre-Trained CNN Models

Abstract: Over the past decade, machine learning techniques, including predictive modeling and pattern recognition, have played a growing role in biomedical sciences, ranging from drug delivery ...
IEEE

SDCnet: a deep learning network model for road segmentation based on CNN and Transformer

Abstract: Road segmentation is a key task in remote sensing semantic segmentation, and the existing deep learning methods still have the problems of insufficient fineness, difficulty in modeling ...
IEEE

A Novel Transformer-CNN Hybrid Deep Learning Architecture for Robust Broad-Coverage Diagnosis of Eye Diseases on Color Fundus Images

Abstract: We present a novel and robust deep-learning architecture that takes into account the pathological characteristics of eye diseases on color fundus images. The proposed hybrid architecture is ...
IEEE

A Deep Learning-Based Approach for Classifying Heart Disease Using CNN on Medical Imaging

Abstract: Heart disease detection from medical images such as X-rays, CT scans, and MRIs is a critical task in the healthcare industry. In this proposed work, we explore the application of ...
IEEE

Privacy-Preserving Autism Detection Using Federated CNN-LSTM Networks: A Spatiotemporal Deep Learning Framework for Decentralized Behavioural Diagnosis

Abstract: Early detection of autism spectrum disorder (ASD) is essential for effective intervention but remains limited by privacy concerns, fragmented data sources, and constrained access to ...
IEEE

Deep Learning for Channel Code Type Recognition

Abstract: Channel code type recognition is critical for enabling receivers to discern codes without prior knowledge. Despite the promise of deep learning approaches in this field, they often encounter ...
GitHub

yc-cui/Deep-Learning-Spatiotemporal-Fusion-Survey

This repository contains a collection of deep learning models for remote sensing spatiotemporal fusion. It includes sections on relevant survey papers, various deep learning model categories, and ...