IEEE

A Semi-supervised Ultrasound Image Segmentation Network Integrating Enhanced Mask Learning and Dynamic Temperature-controlled Self-distillation

Abstract: Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is often degraded by speckle noise, low ...
IEEE

Unlocking Scholarly Insights Using Deep Learning-Based Evaluation Method for Research Impact Assessment in Academic Institutions

Abstract: Background: This paper addresses the academic institutions, especially the recently founded Indian Institutes of Technology (IITs), who struggle to appropriately evaluate and communicate ...
IEEE

SPNet: Sparse-mask Prompt-learning Network for Cerebrovascular Segmentation

Abstract: Cerebrovascular segmentation demands a comprehensive understanding of vascular topology from a global perspective on 3D Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images.
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

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

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

FMCNN: Raw-Data Type Identification Using Feature Matrix and CNN

Abstract: This paper introduces FMCNN, a novel classification method that combines a two-dimensional feature matrix capturing raw data characteristics with a CNN-based classifier. Raw data are the ...
IEEE

Segmentation of Skin Lesions from Medical Images Using a Fusion of CNN and RNN Models

Abstract: The necessity for accurate detection of skin cancer has led to very significant advances in medical image analysis, mainly through the application of deep learning models. Detection of early ...
IEEE

An Integrated CNN-BiLSTM-Transformer Framework for Improved Anomaly Detection Using Surveillance Videos

Abstract: Surveillance cameras have been widely used for monitoring in both private and public sectors as a security measure. Close Circuits Television (CCTV) Cameras are widely used to surveillance ...
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 ...