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implementation for paper "ShelfNet for fast semantic segmentation"
TorchGeo is a PyTorch library designed for deep learning on geospatial data, providing a framework for building and training neural networks for tasks such as semantic segmentation, object detection, and change detection. It serves as a comprehensive pipeline for remote sensing, featuring specialized dataset loaders and multispectral image preprocessing tools. The library is distinguished by a dedicated remote sensing model zoo and extensive support for transfer learning, allowing users to integrate pre-trained weights optimized for specific satellite sensors. It also includes support for sel
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at .
Segmentation-Aware Convolutional Networks Using Local Attention Masks
TernausNetV2: Fully Convolutional Network for Instance Segmentation
The main features of ternaus/ternausnetv2 are: Geospatial Machine Learning, Segmentation Architectures.
Projects with overlapping indexed features include: juntang-zhuang/shelfnet — implementation for paper "ShelfNet for fast semantic segmentation". torchgeo/torchgeo — TorchGeo is a PyTorch library designed for deep learning on geospatial data, providing a framework for building and… aayushbansal/pixelnet — The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More… aitorzip/keras-icnet — Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. akirasosa/mobile-semantic-segmentation — Real-Time Semantic Segmentation in Mobile device. aharley/segaware — Segmentation-Aware Convolutional Networks Using Local Attention Masks.