A Meta Search Space for Encoder Decoder Networks
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Updated
Jan 20, 2021 - Python
A Meta Search Space for Encoder Decoder Networks
Utilizing U-NET deep-learning to deconvolve Structured Illumination Microscopy (SIM) Images. A clean and concise python implemenation.
3D cerebrovascular volume segmentation in Pytorch.
[Done] All of project and assignment in **Computer Vision** class, Gachon Univ. Spring 2022
This research work basically highlights my undergrad thesis works. In my thesis, I have worked on the BraTS 2020 dataset. My total journey of thesis from building various models to writing paper is presented here.
U-NET implementation for Image Segmentation
An example of easytorch implementation on retinal vessel segmentation.
Monte Carlo dropout method for uncertainty quantification in image segmentation
Model training code for "A seasonally invariant deep transform for visual terrain-relative navigation"
U-Net
Prediction of convecition cell initialization 1 hr before
This repository provides an implementation of semantic segmentation for road networks using PyTorch and the U-Net architecture. It focuses specifically on processing aerial images from the Massachusetts dataset.
3D virtual staining with 2D and 2.5D U-Nets
crystal structure analysis with RHEED and ML
Indian Driving Dataset is a very challenging data. Semantic Segmentation is using Deep Learning Method is used for the IDD dataset
Land cover classification in Tanzania using ensemble labels and high resolution Planet NICFI basemaps and Sentinel-1 time series.
U-Net and SegNet
Convolutional Neural Network for Leaf Photo Reconstruction
U-Net based segmentation of CRC tiles and classification for nodal status
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