deenuy / se-imagenet

A large-scale repository of images for software-specific lexicons database called 'SE-ImageNet' to complement software engineering communities and computer vision researchers

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SE-ImageNet

Deenu summer research 2021 work - Preparing a large-scale repository of images for software-specific lexicons called 'SE-ImageNet' constructed on top of SE thesaurus ontology. Our effort on creation of SEImageNet database can provide the communities to excel in software engineering and offer unparalleled opportunities to researchers in the computer vision community and beyond.

This project aims to populate the 104376 classes or synonym sets for software-specific terms with an average of 500 high resolution images per term.

References

  • Caliandro, A., & Graham, J. (2020). Studying Instagram Beyond Selfies. Social Media + Society. https://doi.org/10.1177/2056305120924779
  • Shaowei Wang, David Lo, and Lingxiao Jiang. (2013, March). An empirical study on developer interactions in StackOverflow. In Proceedings of the 28th Annual ACM Symposium on Applied Computing (SAC '13). Association for Computing Machinery, New York, NY, USA, 1019–1024. DOI:https://doi.org/10.1145/2480362.2480557
  • X. Chen, C. Chen, D. Zhang and Z. Xing. (2015, August) "SEthesaurus: WordNet in Software Engineering," in IEEE Transactions on Software Engineering, doi: 10.1109/TSE.2019.2940439
  • Fei Fei, L. (2015, March). How we teach computers to understand pictures? [Video]. TED Conferences. https://youtu.be/40riCqvRoMs

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A large-scale repository of images for software-specific lexicons database called 'SE-ImageNet' to complement software engineering communities and computer vision researchers


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Language:Python 86.0%Language:Jupyter Notebook 13.9%Language:Batchfile 0.1%