IEEE

Deep Fake Detection Using Hybrid CNN and Machine Learning Techniques

Abstract: Deepfake Detection is a critical task that involves the identification of manipulated media using advanced AI techniques. This is essential for preserving trust in the media's integrity and ...
IEEE

Vision Transformer for Diabetic Retinopathy Diagnosis: A Deep Learning Approach Beyond CNN

Abstract: Automated retinal disease detection, particularly in Diabetic Retinopathy (DR) classification, has received significant attention. While Convolutional Neural Networks (CNNs) have been the ...
IEEE

Deep Learning-Based Fault Diagnosis in Quadcopter Actuators: A CNN-LSTM Network with Bayesian Optimization

Abstract: In recent years, deep neural networks have shown promising results in modern fault diagnosis. This paper focuses on diagnosing actuator faults in quadcopters using a deep learning strategy.
IEEE

Deep Learning-Enabled System Diagnosis in Microgrids: A Feature-Feedback GAN Approach

The increasing integration of inverter-based resources (IBRs) and communication networks has brought both modernization and new vulnerabilities to the power system infrastructure. These ...
IEEE

Lightweight Deep Learning Model for Breast Cancer Malignancy Prediction Using CNN on Embedded Edge Devices

Accurate diagnosis of breast cancer in a timely manner will be a key step to have the right treatment. This study suggests a minimalistic CNN architecture for malignancy prediction intended to be ...
IEEE

Faster R-CNN vs SSD: A Deep Learning Approach for Nodule Detection in Lung Cancer Diagnosis

Abstract: Deep learning-based object identification technology has numerous uses, including facial recognition, commercial analytics, and medical imaging analysis. An object detector has a backbone ...
IEEE

CViTM-Net: A Hybrid Deep Learning Method for Tuberculosis Detection in CT Images

Abstract: Tuberculosis (TB) persists as a substantial global public health concern, with a considerable number of new cases documented annually. Conventional diagnostic methodologies encounter ...
IEEE

DIR-YOLO: Segmentation of Alveolar Bone and Mandibular Canal in CBCT Images for Dental Implant Recommendation

Abstract: In dental implant planning, segmentation of the alveolar bone (AB) and mandibular canal (MC) is essential to identify a safe area for dental implant placement in the edentulous molar region.
IEEE

Kidney Disease Detection and Classification Based on CT Scan Images Using Deep Learning

Abstract: Accurate detection and classification of kidney diseases are crucial within medical image processing for increased diagnostic precision and improved treatment outcomes. This research focuses ...
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

3D CT Liver Images Lesion Extraction and Classification for Using 3D-CNN with GLRLM

Abstract: The imaging technique known as computed tomography (CT) is often considered to be the most reliable way for non-invasive diagnosis. Through the use of three-dimensional (3D) computed ...
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 ...