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pytorch_to_onnx_examples

https://github.com/hslima00/pytorch_to_onnx_examples

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    Found .zenodo.json file
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    Scientific vocabulary similarity
    Low similarity (3.3%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: hslima00
  • Language: Python
  • Default Branch: main
  • Size: 113 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created over 1 year ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

pytorchtoonnx_examples

Extended abstract Thesis paper

Examples created while training and exporting several semantic segmentation models to ONNX format. These models were trained using the FIREFRONT Unified Dataset and they act as baseline models to the FIREFRONT Fire and Smoke benchmark.

ONNX models trained with the public training set of the FIREFRONT benchmark are available in the releases page.

Owner

  • Name: Hugo Lima
  • Login: hslima00
  • Kind: user
  • Location: Portugal

Cadet at Portuguese Air Force Academy. Currently studying Electrical Engineering and Computers at Instituto Superior Técnico. 🎓

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
  - family-names: "Lima"
    given-names: "Hugo"
    orcid: "https://orcid.org/0009-0008-0361-8160"  # Replace with your ORCID if available
title: "PyTorch to ONNX Examples"
version: 1.0.0
date-released: 2024-10-20
url: "https://github.com/hslima00/pytorch_to_onnx_examples"
repository-code: "https://github.com/hslima00/pytorch_to_onnx_examples"
license: MIT  # Replace with the actual license you're using
type: software
description: "Examples created while training and exporting several semantic segmentation models to ONNX format. These models were trained using the FIREFRONT Unified Dataset and they act as baseline models to the FIREFRONT Fire and Smoke benchmark."
keywords:
  - pytorch
  - onnx
  - semantic-segmentation
  - fire-detection
  - smoke-detection
  - deep-learning

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