IEEE

FSDA-DETR: Few-Shot Domain-Adaptive Object Detection Transformer in Remote Sensing Imagery

Abstract: Few-shot domain-adaptive object detection (FSDAOD) aims to transfer knowledge from a source domain to a target domain with limited labeled data, which faces severe challenges in the field of ...
IEEE

P4-INT-Based Network Intrusion Detection Method Using CNN-BiLSTM with Multi-Head Attention

Abstract: With the widespread use of Internet services, the risk of cyber attacks has increased significantly. Existing anomaly-based network intrusion detection systems suffer from slow processing ...
IEEE

Vitamin Deficiency Detection Using CNN-Based Image Analysis of Skin, Tongue and Nails

Abstract: Vitamin deficiency is a widespread global health issue that affects millions, often leading to severe physiological and dermatological complications. Early detection is essential for timely ...
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 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

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

Lightweight Multiscale Feature Fusion and Multireceptive Field Feature Enhancement for Small Object Detection in the Aerial Images

Abstract: Small uncrewed autonmous vehicles (UAVs) equipped with deep learning models are increasingly used to detect small objects both on the ground and in aerial environments. Since small objects ...
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.
IEEE

Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm

Abstract: Image steganography conceals secret data within a cover image to generate a new image (stego image) in a manner that makes the secret data undetectable. The main problem in image ...
IEEE

Temporal-Spatial Feature Extraction in IoT-Based SCADA System Security: Hybrid CNN-LSTM and Attention-Based Architectures for Malware Classification and Attack Detection

Abstract: This research presents a Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) model developed for malware classification from IoT devices in the SCADA system and for ...