Minkang Zhang Improves Medical Image Recognition Through RNN Optimization and Deep Learning Integration

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...
IEEE

Efficient Document Image Classification Using Deep Learning Enhance with CNN Architectures

Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
Frontiers

Enhanced breast cancer diagnosis using modified InceptionNet-V3: a deep learning approach for ultrasound image classification

Introduction: Breast cancer (BC) is a malignant neoplasm that originates in the mammary gland’s cellular structures and remains one of the most prevalent cancers among women, ranking second in ...
Frontiers

Enhancing multi-class neurodegenerative disease classification using deep learning and explainable local interpretable model-agnostic explanations

Introduction: Alzheimer's disease (AD) and Parkinson's disease (PD) are two of the most prevalent neurodegenerative disorders, necessitating accurate diagnostic approaches for early detection and ...
Scientific Research Publishing

Diabetic Retinopathy Detection with Deep Learning: A ResNet-CNN Model Enhanced by Attention Mechanism and Ensemble Learning ()

Diabetic retinopathy (DR), a leading cause of vision impairment worldwide, primarily impacts individuals with diabetes, making early detection vital to prevent irreversible vision loss. Leveraging ...
GitHub

Gaserzaghloul/Sports-Image-Classification-Using-CNN

Built a deep CNN for multi-class sports image classification using a Kaggle dataset. Tuned hyperparameters (layers, dropout, optimizer, batch size, learning rate, weight decay) and trained with early ...