IEEE

UOT-FRCNN: Underwater Object Tracking Using Faster R-CNN with ResNet-50 FPN on the UOT32 Dataset

Abstract: UOT-FRCNN, an underwater object tracking system trained on the UOT32 dataset, is presented in this article. It is built on Faster R-CNN with ResNet-50 FPN. With minimal classification and ...
IEEE

Crispvision: Apple Leaf Disease Detection Using Machine Learning and Deeper CNN

Abstract: Identifying diseases in apple leaves plays a vital role in boosting farm productivity and preventing crop losses. This research introduces a comprehensive approach for classifying images of ...
IEEE

AI-based Circuit Fault Detection and Classification using Python Simulation

Abstract: Electrical circuits play a vital role in industrial, automotive, and power systems, where even minor faults can lead to severe performance degradation or system failure. Traditional fault ...
Scientific Research Publishing

Cybersecurity and Forensic Audio Analysis: Deepfake Detection Based on Mfcc, Audio-Text Disconsistency, and Prosodic Features ()

1 Department of Computer and Instructional Technologies Education, Gazi Faculty of Education, Gazi University, Ankara, Türkiye. 2 Department of Forensic Informatics, Institute of Informatics, Gazi ...
IEEE

Bowstern R-CNN: A Bow-Orientation-Sensitive Ship Object Detector Using Keypoints

In the task of ship detection, convolutional neural networks (CNNs) based on deep learning have achieved remarkable progress. However, two-stage object detectors often overlook critical distinctions ...
IEEE

Commercial Plant Leaf Disease Detection in the Coastal and Malnad Regions of Karnataka using CNN, DenseNet121, and InceptionV3

Abstract: Leaf diseases pose a major threat to the productivity and quality of commercial crops in the coastal and Malnad regions, renowned for their diverse and high-value agricultural practices. In ...
IEEE

Comparative Analysis of Object Detection Algorithms for Bolt Detection: Performance Evaluation of Faster R-CNN, SSD, RetinaNet and YOLOv8n

With the development of Industry 4.0, there is increasing emphasis on automating assembly tasks traditionally performed manually by skilled workers [1]. These tasks often involve fasteners, such as ...
IEEE

Design of an improved model for real-time fault detection and localization using hybrid transformer-CNN and graph neural networks

Abstract: Accurate real-time fault detection, localization, and classification techniques are necessary to maintain grid stability and prevent faults. Traditional techniques have low accuracy rates, ...
IEEE

Early fault detection of motor bearings based on 1D-CNN-LSTM

Abstract: Motor bearings, as core load-bearing components of industrial equipment, account for over 44% of all motor failures, directly impacting production efficiency and equipment safety.
IEEE

Salient Object Detection of Dynamic Night Scenes via Bio-Inspired Spotlight Attention and Hierarchical Edge-Texture Fusion

Abstract: The perception of night scenes is of crucial importance for driving safety. In the dimly lit night environment, as the visibility of objects decreases, both experienced and inexperienced ...
IEEE

CNN vs. Transformer-Based Models for Deepfake Detection: A Comparative Analysis

Abstract: As deepfake technology has rapidly progressed, it has become a concern for media authenticity, cybersecurity, and digital forensics. In this work, we compare and contrast CNNs and ...
IEEE

Comparative Study of CNN Models for Human Action Recognition in Detection Tasks

Abstract: Aiming at the performance optimization of convolutional neural networks in human action recognition tasks, this study constructs a system evaluation framework containing eight typical ...