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 ...
IEEE

AgentUNet:A U-shaped Hybrid Network with CNN-Transformer for Medical Image Segmentation

Abstract: An accurate and efficient medical image segmentation algorithm plays an important role when doctors diagnose diagnosis. Using deep learning methods to tackle medical image segmentation tasks ...
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

Emotion Detection From Distorted Images Using Optimized CNN & GAN

Abstract: Image inpainting is a difficult process that entails visually coherently recreating areas of an image that are missing or contaminated. Producing realistic inpainting outcomes is a ...
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.
IEEE

Deep Learning-based MR Image Segmentation for Brain Tumor Detection using EAU-Net

Abstract: Brain tumor segmentation is essential in medical image analysis, as it contributes directly to early diagnosis and treatment design. Existing methodologies such as Particle Swarm ...
IEEE

iLog 3.0: Estimating Food Volume from 2D Images Using Mask R-CNN and Monocular Depth Estimation

Abstract: To maintain a healthy and balanced lifestyle, it is essential to consume food in proportion to one’s individual needs. The proportions of the food consumed need to be calculated to determine ...
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

Automated Cervical Cell Segmentation using Residual Learning and Attention Mechanism for the Cervical Cancer Diagnosis

Abstract: Cervical cancer, one of the common deadly gynaecological cancers among women, can be prevented by regular screening to detect the existence of any premalignant cervical cells at the ...
TechCrunch

Snapchat’s new Lens lets you create AI images using text prompts

Snapchat is launching a new Lens that lets users create and edit images using a text-to-image AI generator, the company told TechCrunch exclusively. The new “Imagine Lens” is available to Snapchat+ ...
GitHub

FaultSeg3D: using synthetic datasets to train an end-to-end convolutional neural network for 3D seismic fault segmentation

If you would just like to try out a pretrained example model, then you can download the pretrained model and use the 'prediction.ipynb' script to run a demo. On 05/07/2020, new models are uploaded for ...