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main.bib
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main.bib
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@ -1,289 +1,13 @@
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@misc{confluence,
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author = {Atlassian},
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title = {{C}onfluence | {Y}our {R}emote-{F}riendly {T}eam {W}orkspace | {A}tlassian --- atlassian.com},
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howpublished = {\url{https://www.atlassian.com/software/confluence}},
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year = {},
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note = {(Accessed 26-Jun-2023)},
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@online{google-vision-api,
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author ={Google},
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title ={Vision AI | Google Cloud},
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year ={2023},
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url ={https://cloud.google.com/vision?hl=en}
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}
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@misc{jira,
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author = {Atlassian},
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title = {{J}ira | {I}ssue \& {P}roject {T}racking {S}oftware | {A}tlassian --- atlassian.com},
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howpublished = {\url{https://www.atlassian.com/software/jira}},
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year = {},
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note = {(Accessed 26-Jun-2023)},
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}
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@misc{ldap,
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series = {Request for Comments},
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number = 5058,
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howpublished = {RFC 5058},
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publisher = {RFC Editor},
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doi = {10.17487/RFC5058},
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url = {https://www.rfc-editor.org/info/rfc5058},
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author = {Dirk Ooms and Nancy Feldman and Yuji Imai and Wim P. Livens and Dr. Richard H. Boivie},
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title = {{Explicit Multicast (Xcast) Concepts and Options}},
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pagetotal = 35,
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year = 2007,
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month = nov,
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abstract = {While traditional IP multicast schemes (RFC 1112) are scalable for very large multicast groups, they have scalability issues with a very large number of distinct multicast groups. This document describes Xcast (Explicit Multi-unicast), a new multicast scheme with complementary scaling properties: Xcast supports a very large number of small multicast sessions. Xcast achieves this by explicitly encoding the list of destinations in the data packets, instead of using a multicast group address. This document discusses Xcast concepts and options in several areas; it does not provide a complete technical specification. This memo defines an Experimental Protocol for the Internet community.},
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}
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@misc{sky,
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author = {},
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title = {{S}ky {G}roup - {E}urope’s leading direct-to-consumer media and entertainment company --- skygroup.sky},
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howpublished = {\url{https://www.skygroup.sky}},
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year = {},
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note = {(Accessed 26-Jun-2023)},
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}
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@misc{gitlab,
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author = {},
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title = {The DevSecOps Platform | GitLab},
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howpublished = {\url{https://about.gitlab.com/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{jenkins,
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author = {},
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title = {Jenkins},
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howpublished = {\url{https://www.jenkins.io/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{ansible,
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author = {},
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title = {Ansible is Simple IT Automation},
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howpublished = {\url{https://www.ansible.com/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{grafana,
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author = {},
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title = {Grafana: The open observability platform | Grafana Labs},
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howpublished = {\url{https://grafana.com/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{ffmpeg,
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author = {},
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title = {FFmpeg},
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howpublished = {\url{https://ffmpeg.org/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{keepass,
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author = {},
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title = {KeePassXC Password Manager},
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howpublished = {\url{https://keepassxc.org/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{cyberark,
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author = {},
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title = {Identity Security and Access Management Leader | CyberArk},
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howpublished = {\url{https://www.cyberark.com/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{docker,
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author = {},
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title = {Docker: Accelerated, Containerized Application Development},
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howpublished = {\url{https://www.docker.com/}},
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month = {},
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year = {},
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note = {(Accessed on 06/26/2023)}
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}
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@misc{opsview,
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author = {},
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title = {Opsview > Monitoring},
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month = {},
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year = {},
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% TODO check this later
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note = {Image generated, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{grafana_charts,
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author = {},
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title = {Grafana - Files in Flight Dashboard Graphs},
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month = {},
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year = {},
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% TODO check this later
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{actual-intake,
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author = {},
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title = {Dashboard [Jenkins]},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{test-intake,
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author = {},
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title = {Dashboard [Jenkins]},
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howpublished = {},
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month = {},
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year = {},
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note = {Screenshot of the page locally hosted page, (Accessed on 06/29/2023), not accessible}
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}
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@misc{spoglight-api,
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author = {},
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title = {Swagger UI},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{spotlight,
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author = {},
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title = {Spotlight},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{spog,
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author = {},
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title = {Spog},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{spog-report,
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author = {},
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title = {Spog},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{launchpad,
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author = {},
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title = {Launchpad page},
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month = {},
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year = {},
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note = {Screenshot of the page, (Accessed on 06/29/2023), not accessible outside Sky UK}
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}
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@misc{launchpad-code,
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author = {Andre Henriques},
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title = {Screenshot of the Code},
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}
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@misc{devops-vault,
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author = {},
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title = {Devops Vault},
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howpublished = {},
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month = {},
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year = {},
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note = {Screenshot of the page locally hosted page, (Accessed on 06/29/2023), not accessible}
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}
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@misc{typescript,
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author = {},
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title = {TypeScript: JavaScript With Syntax For Types.},
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howpublished = {\url{https://www.typescriptlang.org/}},
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month = {},
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year = {},
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note = {(Accessed on 08/07/2023)}
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}
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@misc{react,
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author = {},
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title = {React},
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howpublished = {\url{https://react.dev/}},
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month = {},
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year = {},
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note = {(Accessed on 08/07/2023)}
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}
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@misc{prisma,
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author = {},
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title = {Prisma | Next-generation ORM for Node.js \& TypeScript},
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howpublished = {\url{https://www.prisma.io/}},
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month = {},
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year = {},
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note = {(Accessed on 08/07/2023)}
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}
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@misc{postgres,
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author = {},
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title = {PostgreSQL: The world's most advanced open source database},
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howpublished = {\url{https://www.postgresql.org/}},
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month = {},
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year = {},
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note = {(Accessed on 08/07/2023)}
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}
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@misc{nginx,
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author = {},
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title = {Advanced Load Balancer, Web Server, \& Reverse Proxy - NGINX},
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howpublished = {\url{https://www.nginx.com/}},
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month = {},
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year = {},
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note = {(Accessed on 08/07/2023)}
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}
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@misc{dockerlogo,
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author = {},
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title = {Press and Media Resources - Docker},
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howpublished = {\url{https://www.docker.com/company/newsroom/media-resources/}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{jenkinslogo,
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author = {},
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title = {jenkins.png (742×1024)},
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howpublished = {\url{https://www.jenkins.io/images/logos/jenkins/jenkins.png}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{typescriptlogo,
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author = {},
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title = {TypeScript: Branding},
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howpublished = {\url{https://www.typescriptlang.org/branding/}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{ansiblelogo,
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author = {},
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title = {logos/logos/ansible.svg at main · gilbarbara/logos},
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howpublished = {\url{https://github.com/gilbarbara/logos/blob/main/logos/ansible.svg}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{reactlogo,
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author = {},
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title = {React},
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howpublished = {\url{https://react.dev/}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{gitlablogo,
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author = {},
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title = {Press kit | GitLab},
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howpublished = {\url{https://about.gitlab.com/press/press-kit/}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{atlassianlogo,
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author = {},
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title = {Logo library - Resources - Atlassian Design System},
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howpublished = {\url{https://atlassian.design/resources/logo-library}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{flasklogo,
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author = {},
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title = {Welcome to Flask — Flask Documentation (1.1.x)},
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howpublished = {\url{https://flask.palletsprojects.com/en/1.1.x/}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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}
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@misc{skyaboutus,
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author = {},
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title = {About Us | Sky Group},
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howpublished = {\url{https://www.skygroup.sky/about-us}},
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month = {},
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year = {},
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note = {(Accessed on 08/10/2023)}
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@article{amazon-rekognition,
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author ={Amazon},
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title ={Image Recognition Software - ML Image & Video Analysis - Amazon Rekognition - AWS},
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year ={2023},
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url ={https://aws.amazon.com/rekognition/}
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}
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\usepackage{graphicx}
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\graphicspath{ {../images for report/} }
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\usepackage[margin=2cm]{geometry}
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\usepackage{hyperref}
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\hypersetup{
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\usepackage[style=numeric,sorting=none,backend=biber]{biblatex}
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\addbibresource{../main.bib}
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\title{
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\normalfont \normalsize \textsc{University of Surrey} \\ %[25pt]
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\Huge Final year project \\
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}
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\author{
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\normalfont \normalsize
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Andre Henriques\\[-3pt] \normalsize
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\today
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}
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% Write the approved title of your dissertation
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\title{Automated image classification with expandable models}
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% Write your full name, as in University records
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\author{Andre Henriques, 6644818}
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\date{}
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%%% Begin document
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\tableofcontents
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\newpage
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% This section should contain an introduction to the problem aims and objectives (0.5 page)
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\section{Introduction}
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Image classification is a useful task in many areas. Currently, there exists a few systems that can do image classification, for example Google's Vision API or Amazon's Rekoginition, which tend to be for more general object recognition and labelling. My plan is to create a generalized image classification solution to automatically generate models with the input dataset with minimal user interaction.
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The system should also allow the user to create expandable models, where the number of classes is not known at the moment of that the model is created. Therefore, the system should allow the user to create models that can expand and reduce.
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This should be done in an efficient, and a change in the number of classes should not result in the entire model retraining.
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\subsection{Aims}
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This project aims to:
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\begin{itemize}
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\item Create a system to automatically create and train models
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\item Create a system to automatically expand and reduce models without fully retraining.
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\item Create a system to automatically to merge modules to increase efficiency
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\end{itemize}
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\subsection{Objectives}
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This project objectives are to:
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\begin{itemize}
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\item Create a system to automatically create and train models
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\item Create a system to automatically expand and reduce models without fully retraining.
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\item Create a system to automatically to merge modules to increase efficiency
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\end{itemize}
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\section{Literature Review}
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There currently exist systems that do image classification, like Google Vision AI, and Amazon's Rekoginition. Their tools, while providing similar services to what my project is supposed to do, it mostly focusses on general image classification rather than specific image classification, i.e. Car vs Boat, vs, Car model X vs Car model Y.
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1 page of background and literature review. Here you will need to references things. Gamal et al.~\cite{gamal} introduce the concept of \ldots
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\section{Technical overview}
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1 page of overview. My approach is shown in Figure~\ref{fig:sample}. You can draw the diagram in powerpoint and save the picture
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\section{Workplan}
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The following work plan is what I will be using for the project is shown in Figure~\ref{fig:sample2}.
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\appendix
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\newpage
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\section{References}
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\bibliographystyle{IEEEtran}
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\printbibliography[heading=none]
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% TODO add my job title
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\end{document}
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