IEEE

A Hybrid Approach for Detection of Anomalies in Surveillance Videos using ConvLSTM and Mask R-CNN

Abstract: In recent days automatic detection of anomalies from surveillance scenes have become major research. Though various deep learning algorithms are being developed, it is still difficult for ...
IEEE

PCB Defect Detection Using Machine Learning: YOLOv5 and Inception v3 CNN-Based Approach

Abstract: Identification of PCB board defects early in the manufacturing process is crucial, as PCB quality control plays an important role in the electronics manufacturing industry. Defective PCBs ...
IEEE

A Comprehensive Framework for Accident Detection and Risk Assessment Using CNN and Graph-Based Analytics

Abstract: This proposed work introduces a comprehensive accident detection and risk assessment system that coordinate the strengths of Convolutional Neural Networks (CNNs) and a graph-based analytical ...
IEEE

A Parallel Fusion of CNN and Transformer for CT Lung Nodule Detection

Abstract: To improve the precision of CT lung nodule detection, this paper presents a parallel fusion model based on CNN and Transformer network, which integrates features of the two networks to fully ...
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

Comparison of CNN Model with Different Machine Learning Models for Fake News Detection

Abstract: Fake news continues to be a critical issue in today's era for any citizen concerned about political integrity and the state of governance. The use of internet has experienced exponential ...
IEEE

AI-Powered Lung Cancer Detection: CNN-SVM Hybrid Model with Statistical Insights

Abstract: Liability of lung cancer as a primary cancer mortality agent around the world makes it vital to create diagnostic systems that guarantee both accuracy and operational efficiency. This ...
IEEE

Faster R-CNN in Healthcare and Disease Detection: A Comprehensive Review

Abstract: This review examines the applications, challenges, and prospects of Faster Region-based Convolutional Neural Networks (Faster R-CNN) in healthcare and disease detection. Through a ...
IEEE

Cross-Domain Multilevel Feature Adaptive Alignment R-CNN for Insulator Defect Detection in Transmission Lines

Abstract: Insulator defect detection is a crucial task in the intelligent inspection of transmission lines. Currently, there are challenges such as insufficient image samples and difficulties in ...
IEEE

An Interference Detection Method Based on CNN and CNR for GNSS

Abstract: Global Navigation Satellite System (GNSS) signals are inherently weak and highly susceptible to jamming. Traditional signal analysis-based detection methods struggle with accurate ...
IEEE

Deep Learning-Based Malaria Detection: A Robust CNN Framework for Accurate and Automated Diagnosis

Abstract: This research suggests a strong framework for automated malaria detection using a Convolutional Neural Network (CNN) model. The dataset, sourced from Kaggle, consists of 27,558 ...
IEEE

HTC-HAD: A Hybrid Transformer-CNN Approach for Hyperspectral Anomaly Detection

Abstract: Hyperspectral anomaly detection (HAD) identifies anomalies by analyzing differences between anomalies and background pixels without prior information, presenting a significant challenge.