IEEE

CNN-Based Plant Disease Classification: An Image Analysis Approach

Abstract: The agriculture industry faces significant challenges in maintaining sustainable plant growth while combating diseases that threaten crops. Traditional disease prevention methods rely on ...
IEEE

Hybrid Deep Learning Approach for Heart Disease Prediction using Multi-Head Attention Network and Stacked Long Short-Term Memory

Abstract: Heart disease (HD) is a specific abnormal condition that includes disorders occurring in the heart and affecting the bloodstream, while insufficient blood vessel function impacts heart ...
IEEE

Probabilistic Forecasting for Battery Health Estimation Using CNN-LSTM on Augmented Multi-Operation Data

Abstract: Ensuring the safety and reliability of electric vehicles and energy storage systems requires an effective evaluation of lithium-ion battery State of Health (SOH). Most current methods are ...
IEEE

An Ensemble Deep Learning Model Using CNN, LSTM and Autoencoder for EEG-Based Parkinson’s Disease Classification

Abstract: Parkinson's disease is a neurological disorder hat effects the movements including shaking, stiffness, difficulty while walking and speaking. This condition will occur when the nerve cells ...
IEEE

A Hybrid CNN-ViT and GAN (HCVGAN) Model for Cocoa Leaf Disease Prediction

Abstract: Plant diseases pose a significant risk to farmers and impact crop yield and food safety. Early detection is crucial. In the proposed method, Vision Transformers (ViTs) and Convolutional ...
IEEE

CNN-GRU Based Pedestrian Trajectory Prediction for Smart Cities

Abstract: Pedestrian trajectory prediction is a critical component of smart city applications, including autonomous driving, crowd monitoring, and urban planning. Accurately forecasting pedestrian ...
IEEE

Deep Learning Models for Precision Agriculture: Evaluating CNN Architectures for Accurate Plant Disease Detection

Abstract: Early and precise detection of plant diseases is crucial for enhancing crop yield and minimizing agricultural losses. This paper evaluates the performance of deep learning-based ...
IEEE

Heart Disease Prediction Using Knowledge Graphs

Abstract: This work demonstrates how to improve the prediction of heart illness by integrating ML models with knowledge graphs. By leveraging knowledge graphs to represent the relational structure ...
IEEE

Fault diagnosis of CNC machine tool spindle based on SSA-CNN-Transformer

Abstract: Aiming at the fault diagnosis of CNC machine tool spindle bearing, a fault diagnosis method of CNC machine tool spindle bearing based on SSA-CNN-Transformer is proposed. First, the vibration ...
IEEE

CNN-LSTM-Attention based Predictive Model for Thermal Error in CNC Machine Tool Spindles

Abstract: Aiming at the problem that most thermal error prediction models for machine tools adopt a single neural network architecture, which is difficult to ...