IEEE

An Explainable Approach to Land-Use Classification Using CNN-LSTM and LIME

Abstract: The evolution of landscapes has opened the opportunity to utilize previously unused land for various purposes, such as agriculture and urban development. This approach promotes sustainable ...
IEEE

Deep Learning for Skin Cancer Detection: Multi-Class Lesion Classification Using CNN Architecture

Abstract: Skin cancer ranks among ubiquitous malignancies, its prevalence escalating due to ecological shifts and protracted ultraviolet (UV)exposure. This study aims to address the pressing need for ...
IEEE

Analysis of Microscopic Data on the Behavior of Metallic Nickel Ore During Magnetic Enrichment Using SAM2 and Tensor Decomposition-Based Zero-Shot Image Segmentation

Abstract: The accurate separation and classification of minerals are crucial for integrating deep learning-based computer vision approaches into mineral enrichment processes. In this work, labeled ...
IEEE

AP-Net: Semi-Supervised Ultrasound Cardiac Segmentation Using Enhanced Anatomical Prior

Abstract: Semi-supervised segmentation is gaining popularity in medical image analysis due to challenges in data acquisition and annotation. However, most methods focus on generating additional ...
Frontiers

MLVI-CNN: a hyperspectral stress detection framework using machine learning-optimized indices and deep learning for precision agriculture

Department of Electronics Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India Introduction: Early and accurate detection of crop stress is vital for ...
IEEE

A Novel Approach for Personalized DLPFC Localization in Neuroimaging and Brain Stimulation Using Mask R-CNN

Abstract: The exact location of the left dorsolateral prefrontal cortex (DLPFC) is important for proper brain stimulation and neuroimaging in neuropsychiatric work. Despite its significance, ...
IEEE

IoT-Enabled Real Time Air Quality Monitoring Using Hybrid CNN-RNN with Attention Mechanism

Abstract: Monitoring the environment, particularly air quality, is vital for protecting public health, ensuring safety, and effectively reducing pollution levels. However, using physical models often ...
IEEE

LSTA-CNN: A Lightweight Spatiotemporal Attention-Based Convolutional Neural Network for ASD Diagnosis Using EEG

Abstract: Electroencephalography (EEG) is an effective assessment tool to identify autism spectrum disorders with low cost, and deep learning has been applied in EEG analysis for extracting meaningful ...
IEEE

Research on Coal Quality Using Near-Infrared Spectroscopy Based on Machine Learning

Abstract: Near-Infrared Spectroscopy (NIRS) is widely used in coal quality analysis due to its advantages of fast detection speed, non-destructive nature, and environmental friendliness. However, ...
GitHub

Mask R-CNN Instance Segmentation with OpenCV

This project demonstrates instance segmentation using Mask R-CNN with the OpenCV DNN module. The model is pre-trained on the COCO dataset and can detect and segment multiple object classes in images.
GitHub

Pull requests: srirammulukuntla11/Instance-Segmentation-using-Mask-R-CNN-with-Python-and-OpenCV

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
IEEE

Rice Disease Detection and Classification Using Mask R-CNN and DenseNet

Abstract: Rice is an essential crop in the world food supply. As the consumption of rice grows, its production has fallen due to diseases. These diseases are able to spread quickly, leading to ...