IEEE

A Facial Deepfake Detection Approach using CNN-based Models, Swin Transformer and Classifier Fusion

Abstract: Facial deepfake detection focuses on identifying manipulated images and videos generated by deep learning methods such as Generative Adversarial Networks (GANs) and autoencoders. Detection ...
IEEE

Underwater Marine Debris Detection: A Lightweight CNN-Based Binary Classifier

Abstract: Marine debris poses a significant threat to aquatic ecosystems, with underwater garbage detection emerging as a critical challenge for environmental protection. This paper presents a ...
IEEE

FPGA Implementation of CNN-Based Pulmonary Disease Classifier for Low-Cost Diagnostic Platforms

Abstract: The paper introduces the design and FPGA implementation of a convolutional neural network (CNN)-based, low-cost and low-energy diagnostic platform that classifies pulmonary diseases. The ...
IEEE

Joint Optimization of CycleGAN and CNN Classifier for COVID-19 Detection and Biomarker Localization

Abstract: The COVID-19 has caused mass casualties due to its rapid spread and lack of vaccines. Pathological lesions in lungs caused by COVID-19 is the main symptom which are easier to be detected ...
GitHub

sms-classifier

Real-time SMS text classification using Neural Networks and Deep Learning. Features 97%+ accuracy and a responsive web interface. A simple SMS spam classifier that cleans text, converts it using ...
IEEE

A comparative analysis of Alzheimer’s Disease by Pre-Trained CNN Classifiers using Two Palnes of MRI Images

Abstract: Alzheimer’s Disease (AD) is a progressive neurological disorder that leads to significant deterioration in cognitive functions and memory. AD is accompanied by many symptoms like memory loss ...
IEEE

Fuzzy Integral-Based CNN Classifier Fusion for 3D Skeleton Action Recognition

Abstract: Action recognition based on skeleton key joints has gained popularity due to its cost effectiveness and low complexity. Existing Convolutional Neural Network (CNN) based models mostly fail ...
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 ...