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#

stanford-cars

Here are 20 public repositories matching this topic...

This is a PyTorch implementation of the paper "Multi-branch and Multi-scale Attention Learning for Fine-Grained Visual Categorization (MMAL-Net)" (Fan Zhang, Meng Li, Guisheng Zhai, Yizhao Liu).

  • UpdatedDec 29, 2020
  • Python

PyTorch custom dataset APIs -- CUB-200-2011, Stanford Dogs, Stanford Cars, FGVC Aircraft, NABirds, Tiny ImageNet, iNaturalist2017

  • UpdatedDec 18, 2022
  • Python

Train a TensorFlow deep learning model to detect vehicle make/model.

  • UpdatedJan 30, 2022
  • Python

Fine-Grained Visual Classification on Stanford Cars Dataset

  • UpdatedJun 21, 2022
  • Jupyter Notebook

PyTorch MobileNetV2 Stanford Cars Dataset Classification (0.85 Accuracy)

  • UpdatedJul 14, 2022
  • Jupyter Notebook

Uncertainty quantification method and tool for object detection models

  • UpdatedNov 20, 2021
  • Jupyter Notebook

Deep Learning experiments for the Stanford Cars dataset

  • UpdatedMar 24, 2023
  • Python

Car Classification with 89% accuracy using ResNet50 with PyTorch & FastAI.

  • UpdatedSep 27, 2020
  • Jupyter Notebook

Enhanced class label granularity of the Stanford Cars dataset.

  • UpdatedMay 11, 2024
  • Python

Multi-class classification on Stanford Cars Dataset

  • UpdatedMay 26, 2023
  • Python

Project that detects the model of a car, between 1 and 196 models ( the 196 modelss of Stanford car file), that appears in a photograph with a success rate of more than 70% (using a test file that has not been involved in the training as a valid or training file, "unseen data") and can be implemented on a personal computer.

  • UpdatedFeb 9, 2024
  • Python
CAM_Stanford_Cars

Class Activation Map | Stanford Cars | PyTorch

  • UpdatedJan 5, 2023
  • Python

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