Frontiers

Artificial intelligence and deep learning for neural data analysis

Artificial intelligence and deep learning have revolutionized the field of neural data analysis in recent years. The explosion of complex, high-dimensional ...
IEEE

Classification of Music Genres based on Machine Learning SVM and CNN

Abstract: This study aims to compare the performance of two classification methods—Support Vector Machine (SVM) and Convolutional Neural Network (CNN)—in identifying music genres based on audio data ...
IEEE

A Multimodal Deep Learning Model Integrating CNN and Transformer for Predicting Chemotherapy-Induced Cardiotoxicity

Abstract: Chemotherapy-induced cardiotoxicity presents a major risk to cancer patients, often leading to severe cardiac complications such as heart failure, myocardial infarction, and arrhythmias.
IEEE

Design and Analysis of an Enhanced Cnn Accelerator for Deep Learning Applications

Abstract: This paper presents an optimized Convolutional Neural Network (CNN) accelerator with a focus on improving power efficiency and computational performance. Traditional CNN accelerators often ...
IEEE

Intelligent Resume Screening and Candidate Ranking Using CNN-GRU: A Deep Learning Approach for Smarter Recruitment

Abstract: Automated resume screening is a crucial task in modern recruitment, requiring efficient and accurate candidate evaluation. This research proposes a hybrid Convolutional Neural Network-Gated ...
IEEE

Development of Scalable Deep Learning Frameworks Utilizing Advanced Hybrid Models like Transformer-CNN for Distributed Computing Environments

Abstract: Over the past few years especially in the context of communication and information processing the importance of Natural language processing which demands efficient deep learning models has ...
IEEE

Automated Trash Detection and Classification Using CNN: A Deep Learning Approach

Abstract: A research project focuses on creating automated trash detection and classification through convolutional neural networks (CNNs) with an objective to improve waste management systems. The ...
IEEE

Leveraging Deep Learning for Malaria Detection: Multi-Model Comparative Analysis of CNN Architectures with Future Directions for AI-Driven Healthcare

Abstract: Malaria is a serious, life-threatening disease that necessitates early and precise detection for effective treatment. This study assessed the performance of five deep learning ...
IEEE

Deep Reinforcement Learning for Dynamic Resource Allocation : Generalizing Defensive Strategies Based on Pairwise Unit Analysis

Abstract: Managing resource allocation dynamically across varying scenarios is a complex problem that necessitates robust and flexible approaches. In this paper, we propose a deep reinforcement ...
GitHub

Deep Research for Code & Files

Transform your codebase into a searchable knowledge base for AI assistants using semantic search via cAST algorithm and regex search. Integrates with AI assistants via the Model Context Protocol (MCP) ...
IEEE

Deep Learning Approaches for Lung Cancer Detection: A Comprehensive Evaluation of CNN

Abstract: Lung cancer is one of the most prevalent and deadly cancers, characterized by the uncontrolled growth of abnormal cells in the lung tissue. Early detection is critical for improving survival ...
IEEE

Deep Learning-Driven Mobile Application for Rice Crop Disease Detection Using CNN

Abstract: This study presents a deep learning-based mobile app for rice crop disease detection using a MobileNetV2-based CNN model trained on a dataset of 4,700 rice leaf images. The app accurately ...