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Update README
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README.md

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The official implementations of Head Network Distillation (HND) studies for image classification tasks:
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- "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems," [IEEE Access](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639)
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[[PDF (Open Access)](https://ieeexplore.ieee.org/document/9265295)]
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- "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems," [MobiCom 2019 Workshop HotEdgeVideo '19](https://www.microsoft.com/en-us/research/event/the-1st-workshop-on-hot-topics-in-video-analytics-and-intelligent-edges/)
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- "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems," [ACM MobiCom 2019 Workshop HotEdgeVideo '19](https://www.microsoft.com/en-us/research/event/the-1st-workshop-on-hot-topics-in-video-analytics-and-intelligent-edges/)
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[[PDF (Open Access)](https://dl.acm.org/doi/abs/10.1145/3349614.3356022)]
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Part of this repository is used as baselines in the following paper:
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- "BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing," [WoWMoM '22](https://computing.ulster.ac.uk/WoWMoM2022/index.html)
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- "BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing," [IEEE WoWMoM '22](https://computing.ulster.ac.uk/WoWMoM2022/index.html)
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[[Preprint](https://arxiv.org/abs/2201.02693)]
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Looking for **object detection tasks**? Take a look at https://github.com/yoshitomo-matsubara/hnd-ghnd-object-detectors as well

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