Deploying Deep Learning Models via IOT Deployment Tools
Abstract
Deep Learning and Internet of Things (IoT) are some top fields of research in computer science now days. Many researches are going on to incorporate the best of both the fields and to collaborate them into one. Inspired from this, this paper works on using and creating an efficient Deep Learning model for colorizing the image and transport them to remote systems through IoT deployment tools. This paper develops two models, namely Alpha and Beta, for the colorization of the greyscale images. Efficient models are developed to lessen the loss rate to around 0.005. Then the paper uses tools like AWS Greengrass and Docker for the deployment of the model, thus combining Deep Learning with IoT deployment tools.
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Models are commonly made available for serving predictions through a REST or RPC API.
“Models are commonly made available for serving predictions through a REST [12,16,26,29,40,45] or RPC [12,28,45] API.”
From Operationalizing machine learning models: a systematic literature review (2022) · cites this paper as [26]
Docker is by far the most frequently reported solution for packaging ML models in containers.
“Docker 17 is by far the most frequently reported solution [12,16,20,26,28,40,44].”
From Operationalizing machine learning models: a systematic literature review (2022) · cites this paper as [26]
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Operationalizing machine learning models: a systematic literature review
Kolltveit, A. B., & Li, J. (2022) · Proceedings of the 1st Workshop on Software Engineering for Responsible AI · doi:10.1145/3526073.3527584 · Cited by 34 · see citing works
Building A Platform for Machine Learning Operations from Open Source Frameworks
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Gupta, N., Anantharaj, K., & Subramani, K. (2020) · 2020 International Conference on Computer Communication and Informatics (ICCCI) · doi:10.1109/iccci48352.2020.9104073 · Cited by 23 · see citing works
- Authors
- Krishnamurthi, R., Maheshwari, R., & Gulati, R.
- Affiliations
- Jaypee Institute of Information Technology (IN)
- Venue
- 2019 Twelfth International Conference on Contemporary Computing (IC3)
- Publisher
- IEEE
- Published
- 2019-08
- Pages
- 1-6
- ISSN
- 2572-6110 (ISSN-L)
- OpenAlex
- W2973431684
- Cited by
- 6
- References
- 13
- Citations by year
- 2024: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2020: 2
- FWCI
- 0.86
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Contemporary Computing (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Keywords
- image colorization, grayscale image colorization, deep learning model deployment, Internet of Things, Docker, edge computing
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