Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
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Updated
Dec 7, 2024 - Python
Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Segmentation models with pretrained backbones. Keras and TensorFlow Keras.
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
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MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation
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Official repo for Medical Image Segmentation Review: The Success of U-Net
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Official implementation of DoubleU-Net for Semantic Image Segmentation in TensorFlow & Pytorch (Nominated for Best Paper Award (IEEE CBMS))
Meidcal Image Segmentation Pytorch Version
A Python Library for High-Level Semantic Segmentation Models based on TensorFlow and Keras with pretrained backbones.
Segment Anything Model for large-scale, vectorized road network extraction from aerial imagery. CVPRW 2024
This project is about detecting defects on steel surface using Unet. The dataset used for this project is the NEU-DET database.
Contextual Attention Network: Transformer Meets U-Net
A Flutter plugin for managing both Yolov5 model and Tesseract v4, accessing with TensorFlow Lite 2.x. Support object detection, segmentation and OCR on both iOS and Android.
Plugin para ejecutar el modelo de META Segment Anything en QGIS
[AAAI 2023] Official PyTorch implementation of the paper "SLAug: Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation"
[PR] How to Reduce Change Detection to Semantic Segmentation
Quadra: Effortless and reproducible deep learning workflows with configuration files.
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