State-of-the-Art Deep Learning Models in TensorFlow Modern Machine Learning in the Google Colab Ecosystem
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Updated
Jan 24, 2023 - Jupyter Notebook
State-of-the-Art Deep Learning Models in TensorFlow Modern Machine Learning in the Google Colab Ecosystem
Official implementation of DoubleU-Net: A Deep Convolutional Neural Network for Medical Image Segmentation (pytorch implementation)
Classification and segmentation 4 VietNamese foods in using Pytorch
Semantic segmentation is a type of computer vision technique that assigns a label to every pixel in an image. The label indicates the class of object that the pixel represents. Semantic segmentation is used in tasks such as self-driving cars, where it is important to know not only the boundaries of objects, but also what those objects are.
Unveiling the secrets of an ancient library buried by Mount Vesuvius, this Kaggle competition, supported by the Vesuvius Challenge organization, tasked participants with detecting ink from 3D X-ray scans of charred scrolls preserved in a Roman villa in Herculaneum.
Image segmentation task with KiTS19 challenge data using U-net
An attention-based solution on a long-tailed 3D point cloud dataset
Deep learning based semantic segmentation Using the FCN.
road and traffic segmentation with IoU metric and DICE coffecient
This is a warehouse for DeepLabV3-Xception-pytorch-model, can be used to train your segmentation datasets
pre trained deeplabV3 with different backbones
NYU Deep Learning 2023 project for semantic segmentation in video sequences using dual-phase learning with U-Net and ConvLSTM, focusing on predicting segmentation masks from synthetic 3D shape videos.
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