Not a serious implementation of Deep white balance in Tensorflow. Aimed for personal learning.
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Updated
Oct 13, 2022 - Python
Not a serious implementation of Deep white balance in Tensorflow. Aimed for personal learning.
People with pulmonary disease often have a high opacity, which makes segmentation of the lung from chest X-rays more difficult. In this study, I propose a methodology to improve the performance of the U-NET structure so that it is able to extract the features and spatial characteristics of the X-ray images of the chest region.
Kvasir dataset - segmentation
Applying UNET Model on TGS Salt Identification Challenge hosted on Kaggle
Implementation of Segnet, FCN, UNet and other models in Keras.
Employing a fusion of UNet and ResNet architectures, the project endeavors to achieve multiclass semantic segmentation of sandstone images. Through deep learning techniques, it seeks to uncover microstructural features across various geological classifications.
Glaucoma detection using CDR and UNET model to segment optic disk and optic cup.
In this project we used sematic segmentation to detect clouds in satellite captured images
A tiny version of original U-Net architecture was used to detect vehicles with segmentation vehicle classes: car, trailer, bus, rider, motorcycle, truck.
Python tools to perform bathymetric inversion for nearshore areas with video monitoring and deep learning
Dermatologists suffer from the difficulty of locating cancerous and malignant skin lesions, which causes many problems during the process of removing the tumor, which leads to the return of the tumor again. In determining the location of the tumor and its spread and determining the area that must be removed accurately.
speech-enhancement-flask
Lighweight Denoise model
From the MRI scans of brain, identify which are having tumor.
recreation of UNET: Convolutional networks for biomedical image segmentation. Implemented with keras & tensorflow.
Find the nuclei in divergent images to using UNet
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