IEEE

Automated Food Spoilage Detection Using Deep Learning: A CNN-Based Approach

Abstract: Food spoilage detection is critical in ensuring food safety and reducing waste. In this work, we offer a new neural network model, rotOrNot, intended for image analysis-based rotten food ...
IEEE

An Interpretable Machine Learning Model for Leukemia Diagnosis Using CNN-SVM and Explainable AI

Abstract: The method uses a new approach for classifying leukaemia by connecting a CNN with an SVM classifier built especially for the task. Because white blood cell morphology diagnosis is crucial ...
IEEE

Early Radar Work Mode Recognition Using Hybrid CNN-Transformer and Reinforcement Learning

In this paper, a novel approach is proposed for early recognition of Radar Work Mode, which integrates a hybrid CNN-Transformer architecture and a Reinforcement Learning strategy. The model processes ...
IEEE

Predictive Autism Analysis: Integrating CNN and RNN with Ensemble Learning

Abstract: Timely identification of Autism Spectrum Disorder (ASD) is essential for successful intervention, but current diagnostic methods often depend on subjective observations, potentially missing ...
IEEE

Parallel CNN Deep Learning Model for Security Monitoring and Fault Prediction in Electrical Systems

Abstract: Electrical systems keep things running in modern life, but they often run into problems like imbalances, short circuits, ground faults, and overloading, which can cause equipment to break ...
IEEE

Carbon Emission Quantification of Machine Learning: A Review

Abstract: The rapid growth of machine learning (ML) technologies has raised significant concerns about their environmental impact, particularly regarding energy consumption and carbon emissions. This ...
IEEE

A Comparative Analysis of CNN-based Deep Learning Models for Landslide Detection

Abstract: Landslides inflict substantial societal and economic damage, underscoring their global significance as recurrent and destructive natural disasters. Recent landslides in northern parts of ...
IEEE

Privacy-Preserving Federated Learning for Threat Detection Using CNN and Transformer with Homomorphic Encryption

Abstract: Identifying and filtering cybersecurity threats are necessary for data privacy and security. This research proposes a Federated Learning (FL) framework integrated with a Hybrid Deep Learning ...
IEEE

An Explainable Hybrid Deep Learning Framework for Network Intrusion Detection Using Feature-Guided CNN Models

Abstract: Cybersecurity risks have evolved in the linked digital terrain of today into more complex, frequent, and varied forms. Conventional intrusion detection systems sometimes find it difficult to ...
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 ...
CNN

Oil CEOs are meeting with Trump today. These are their demands

President Donald Trump is set to meet with Big Oil executives Friday as part of a weeklong charm offensive to persuade America’s largest energy companies to return to Venezuela. The oil industry has ...
IEEE

Deep Learning for 5G Localization: Hybrid CNN-Transformer Approach in Accuracy Enhancement

Abstract: Accurate localization of user equipments (UEs) in 5G communication systems is critical for maintaining synchronization with the base stations and supporting emerging location-based services.