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Apr 21, 2023 - Jupyter Notebook
vision-transformers
Here are 80 public repositories matching this topic...
A repository containing implementations of famous Vision Architectures over the years
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Sep 27, 2024 - Python
This project focuses on evaluating Convolutional Neural Networks (CNN) and Vision Transformers (ViT) for image classification tasks, specifically distinguishing between Asian elephants and African elephants.
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Apr 8, 2024 - Jupyter Notebook
Implements different 2D object detection algorithms. Compares accuracies.
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Jun 2, 2022
Classifying musical pieces into appropriate genres using CNNs and Vision Transformers
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Oct 22, 2023 - Jupyter Notebook
Vision Transfomer for classifying images
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Mar 20, 2024 - Jupyter Notebook
Testing the Moondream tiny vision model
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May 12, 2024 - Jupyter Notebook
Deep learning pet breed recognition app
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Jul 29, 2024 - Jupyter Notebook
Implemented a Vision Transformer from famous paper 'An Image is Worth 16x16 Images'. Implemented Multi-Head Attention, MLP from scratch in PyTorch.
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Aug 30, 2024 - Python
Benchmark for formally verifying ViTs
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Jul 15, 2024 - Python
Image-based plant identification at global scale.
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Oct 19, 2023 - Python
image-captioning using ViT-PhoBERT model
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Jun 30, 2024 - Jupyter Notebook
This repository accompanies the article entitled "Automated Classification of Oral Cancer Lesions: Vision Transformer vs Radiomics."
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Mar 29, 2024 - Jupyter Notebook
Implementations of transformers based models for different vision tasks
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Jun 30, 2021 - Python
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Feb 28, 2024 - Jupyter Notebook
Based on Dosovitskiy et al., 2020. Final project for DS4440: Practical Neural Networks, Fall 2020.
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Jan 8, 2021 - Python
Final project of the Multidisciplinary course offered at Politecnico di Milano A.Y. 2022/2023
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Jun 15, 2023 - Jupyter Notebook
Streamlit app that performs binary and multiclass classification of gravitational lensing images along with dark matter halo mass prediction.
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Aug 15, 2024 - Jupyter Notebook
PyTorch Implementation of OCR (Object-Contextual Representations)
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Jun 15, 2023 - Python
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