AI Researcher Mahfuz Islam Khan Jabed Advances Ethical, Explainable AI for Workforce and Healthcare Applications

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
IEEE

Deep Learning Approaches to Babylonian Numeral Recognition: A CNN-SVM Hybrid Model

Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...
IEEE

Deep Learning for Multi-Class DDoS Detection in SDNs: A CNN-LSTM Based Approach

Abstract: Recently Distributed Denial of Service (DDoS) attacks have increased extensively, taking about 35% of all cyber threats among which the attack characteristic rises around 300% within the ...
northpennnow

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
IEEE

Image Denoising using CNN in Deep Learning

Abstract: Since noise distribution cannot be predicted, removing mixed noise from a picture is difficult. Additive white Gaussian and impulse noise are the most common mixed noises in noisy images.
IEEE

GRFuzz: A Deep Reinforcement Learning Approach to Python Library Fuzzing with GRPO

In the digital realm, ensuring the security and reliability of systems and software is of paramount importance. Fuzzing has emerged as one of the most effective testing techniques for uncovering ...
IEEE

A Deep Learning Approach for Automated Image Captioning with CNN and LSTM Models

Abstract: Accurately describing a picture has turned out to be a crucial problem, and expert system researchers have always been interested in image captioning, sometimes referred to as characterizing ...
IEEE

Deep Learning-Based Detection and Classification of Copra Cooking Levels Using Faster R-CNN and MobileNet SSD V2

Abstract: This paper explores the performance of two deep learning object detection architectures—Faster R-CNN with Inception V2 and MobileNet SSD V2—for detection and classification of the degree of ...
IEEE

MFC-CNN: A Deep Learning Framework for Urban Building Height Estimation from GF-7 Imagery

Abstract: Estimating building heights by generating disparity maps from multi-view satellite images through stereo matching remains challenging in urban research. However, disparity maps produced by ...