Pinned Repositories
book
:books: All programming languages books
deepglobe_land_cover_classification_with_deeplabv3plus
DeepGlobe Land Cover Classification Challenge
DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
global-canopy-height-model
This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.
Guided-Depth-Map-Super-resolution-A-Survey
Guided Depth Map Super-resolution: A Survey (ACM CSUR 2023)
keras-unet
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
netron
Visualizer for neural network, deep learning, and machine learning models
Paraformer
Paraformer ()
personal_project
A presentation of personal projects
pytorch-image-classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Naughtyba's Repositories
Naughtyba/book
:books: All programming languages books
Naughtyba/deepglobe_land_cover_classification_with_deeplabv3plus
DeepGlobe Land Cover Classification Challenge
Naughtyba/DeepLearning
深度学习入门教程, 优秀文章, Deep Learning Tutorial
Naughtyba/global-canopy-height-model
This repository contains the code used in the paper: A high-resolution canopy height model of the Earth. Here, we developed a model to estimate canopy top height anywhere on Earth. The model estimates canopy top height for every Sentinel-2 image pixel and was trained using sparse GEDI LIDAR data as a reference.
Naughtyba/Guided-Depth-Map-Super-resolution-A-Survey
Guided Depth Map Super-resolution: A Survey (ACM CSUR 2023)
Naughtyba/keras-unet
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from multiple projects I performed working on semantic segmentation tasks
Naughtyba/netron
Visualizer for neural network, deep learning, and machine learning models
Naughtyba/Paraformer
Paraformer ()
Naughtyba/personal_project
A presentation of personal projects
Naughtyba/pytorch-image-classification
Tutorials on how to implement a few key architectures for image classification using PyTorch and TorchVision.
Naughtyba/SegLoss
A collection of loss functions for medical image segmentation
Naughtyba/stl_prd
Naughtyba/VPD
[ICCV 2023] VPD is a framework that leverages the high-level and low-level knowledge of a pre-trained text-to-image diffusion model to downstream visual perception tasks.