IEEE

An Evaluation of Medical Image Analysis using Image Segmentation and Deep Learning Techniques for Brain-Tumour

Abstract: An aberrant mass of rapidly proliferating brain cells, known as a brain tumour, may develop into various forms of cancer. The segmentation of brain tumours by MRI scans is a challenging but ...
IEEE

Efficient Satellite Image Retrieval Using Shearlet Transforms and Spiking Neurons-Based Liquid Autoencoder Model

Abstract: This paper introduces an innovative content-based image retrieval system for precise and effective retrieval of satellite images. The system integrates liquid autoencoders with shearlet ...
IEEE

Brain MRI Analysis Using CNN-Based Feature Extraction and Machine Learning Techniques to Diagnose Alzheimer's Disease

Abstract: This research focuses on developing a complex framework for automatic diagnosis purposes of Alzheimer's disease from MRI brain data, with emphasis placed on advancement in accuracy towards ...
IEEE

3D Reconstruction of Steel Rail using Multi-view Cameras and Mask R-CNN

Abstract: This study proposed a method that integrates multi-view image processing, depth estimation, and point cloud generation to accurately reconstruct a 3D model of a rail. The method is tested by ...
IEEE

Physically-Aware Qubit Reuse for Optimized Quantum Circuit Compilation Using Machine Learning

Recently developed quantum computers support mid-circuit measurements, allowing qubit measurement, resetting, and reuse during the execution of quantum circuits. This capability opens new ...
IEEE

Fully Perturbed Self-Ensemble Framework using Cascaded Parallel CNN-Transformer for Semi-Supervised Medical Image Segmentation

Abstract: Semi-supervised learning (SSL) has achieved remarkable progress in the field of medical image segmentation (MIS), but it still faces two main challenges. First, the consistency learning ...
IEEE

Data-Driven Customer Segmentation in E-Commerce using K-Means Clustering for Personalized Marketing Strategies

Abstract: With the big data era, precision marketing in e-commerce has become ever more important in order to target prospective customers with high relevance. The present research focuses on applying ...
IEEE

Automatic Extraction of Tooth Region for Dental Aesthetic Treatment Using Mask R-CNN

Abstract: In recent years, there has been an increasing interest in the aesthetics of teeth, particularly regarding tooth color. Among the various approaches to improve the appearance of teeth, crown ...
IEEE

Deep Learning for Satellite Image Classification: A Comparative Analysis of CNN and ResNet-18

Abstract: With the ease of classifying land through satellite imaging, remote sensing has captured the Earth observation domain. Traditional methods for analyzing satellite images relied on manual ...
IEEE

Deep Learning Based Segmentation of Weed Images in crop fields using U-Net

Abstract: Weeds are problems for crop yields because they exert harmful effects on the yields by competing with cultivated crops for necessary resources like nutrients, sunlight, and soil. As a result ...
IEEE

Optimized Ensemble Learning for Semantic Segmentation of Satellite Imagery Using DeepLabV3+ and UNet With PSO and Cross-Dataset Evaluation

Abstract: Semantic segmentation is critical in remote sensing applications such as urban planning, disaster management, and environmental monitoring. However, segmenting complex satellite images ...
psypost.org

Scientists use machine learning to control specific brain circuits

A team of researchers in Japan has developed an artificial intelligence tool called YORU that can identify specific animal behaviors in real time and immediately interact with the animals’ brain ...