IEEE

Coronary Heart Disease Prediction Using CNN, RNN, LSTM and Attention DNN Model

Abstract: Coronary Heart Disease popularly referred to as CHD is one of the leading causes of death and illness across the global population making it imperative for the identification of an effective ...
IEEE

Mask augmented Object-Centric Contrastive Learning for Amodal Instance Segmentation

Abstract: Human cognition is robust in estimating depth ordering and occluded regions of objects, including amodal instance segmentation (AIS). Object-centric representation learning (OCRL) is an ...
IEEE

MCBTNet: Multi-Feature Fusion CNN and Bi- Level Routing Attention Transformer-Based Medical Image Segmentation Network

Abstract: Accurate medical image segmentation is crucial for precise diagnosis and treatment in clinical pathology analysis and surgical navigation. While Convolutional Neural Network (CNN)-based ...
IEEE

Enhancing IIoT Security Using Hybrid CNN-BiLSTM Models with Blockchain Integration

Abstract: In the rapidly evolving Industrial Internet of Things (IIoT) landscape, ensuring robust security measures for detecting and mitigating cyber threats is paramount. This paper suggests a ...
IEEE

Improving the Sound Classification Accuracy Using CNN-LSTM and MFCC with Audio Augmentation for Diagnosing Respiratory Disease

Abstract: Audio is vital information data for understanding various situations. A multitude of sound features can be explained by analysis through the audio signals. Numerous classification methods ...
IEEE

Dense Segmentation Techniques Using Deep Learning for Urban Scene Parsing: A Review

Abstract: Dense segmentation tasks, including semantic, instance, and panoptic segmentation, are essential for improving our comprehension of urban landscapes. This paper examines various deep ...
IEEE

Fruit Quality Monitoring System using CNN

Abstract: The grading of fruits relies on inspections, experiences, and observations, with a proposed system integrating machine learning techniques to assess fruit freshness. By analyzing 2D fruit ...
IEEE

Fake Image Detection in Fake News Using Convolutional Neural Network (CNN)

Abstract: ’Fake news’ refers to false, inaccurate, or misleading information that spreads as real news. Fake news primarily aims to affect societies and individuals by spreading false or misleading ...
IEEE

Intrusion Detection in IoT and IIoT: Comparing Lightweight Machine Learning Techniques Using TON_IoT, WUSTL-IIOT-2021, and EdgeIIoTset Datasets

Abstract: The security of Internet of Things (IoT) and Industrial Internet of Things (IIoT) systems has been significantly enhanced through the integration of effective intrusion detection systems ...
IEEE

Sentiment Analysis for E-Commerce Product Reviews Using CNN-LSTM

Abstract: Due to the exponential growth of the number of user-generated reviews on e-commerce platforms, sentiment analysis has emerged for analyzing consumer opinions. This study aims to classify ...
IEEE

Fake Image Detector using Machine Learning

Abstract: The detection of fake images has become increasingly critical due to the proliferation of deepfakes and sophisticated image manipulation techniques used for misinformation, fraud, and public ...
IEEE

Asymmetric Mamba–CNN Collaborative Architecture for Large-Size Remote Sensing Image Semantic Segmentation

Large-size remote sensing images contain rich geographical information. Efficient and accurate semantic segmentation of these images is of significant importance in various fields. However, the ...