This project was developed as a part of the presentation that I gave on the Programming 2.0 webinar: Autonomous driving.
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Updated
Jan 20, 2021 - Python
This project was developed as a part of the presentation that I gave on the Programming 2.0 webinar: Autonomous driving.
Deep Convolutional Encoder-Decoder Architecture implemented along with max-pooling indices for pixel-wise semantic segmentation using CamVid dataset.
This is a project on semantic image segmentation using CamVid dataset, implemented through the FastAI framework.
Репозиторий для обучения нейросетевых моделей по семантической сегментации + пример использования моделей на практике
Training a model using UNET and ResNet34 to do image segmentation on street images
Deep Convolutional Encoder-Decoder Architecture implemented along with max-pooling indices for pixel-wise semantic segmentation using CamVid dataset.
Semantic segmentation on CamVid dataset using the U-Net.
Image Segmentation by Iterative Inference from Conditional Score Estimation
fast semantic segmentation with Enet
MATLAB implementation of popular image segmentation algorithms
Pytorch Implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation (https://arxiv.org/abs/1606.02147)
Deep learning semantic segmentation on the Camvid dataset using PyTorch FCN ResNet50 neural network.
Adapted representation of synthetic data to real world data.
This is the DL repository for Semantic Segmentation using U-Net model in pytorch library.
Applying the 100 Layer Tiramisu on the Camvid Dataset
Semantic Segmentation using Tensorflow on popular Datasets like Ade20k, Camvid, Coco, PascalVoc
Tensorflow 2 implementation of complete pipeline for multiclass image semantic segmentation using UNet, SegNet and FCN32 architectures on Cambridge-driving Labeled Video Database (CamVid) dataset.
This is the official repository for our recent work: PIDNet
A pytorch-based real-time segmentation model for autonomous driving
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