dc.contributor.author | Fonseka, G. S. D | |
dc.date.accessioned | 2022-03-08T06:30:00Z | |
dc.date.available | 2022-03-08T06:30:00Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Fonseka, G. S. D (2021) Identify Tea Stem & Branch Diseases Found in Sri Lanka Using Image Processing. BSc. Dissertation Informatics Institute of Technology | en_US |
dc.identifier.issn | 2016122 | |
dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/878 | |
dc.description.abstract | " Intelligence has evolved so much within today’s context so much more that it has the ability to think for us and even figure what we like more than our own knowledge. What movie should I watch next? what product would be beneficial for me to purchase along with this? Are a couple of questions that are very well been answered for us by computers in todays context. With that been said, is entertainment the only domain in which we can rely on a computer to give a suggestions? Why can’t be leverage technology to give us answers to questions we ask ourselves in our professional careers which potentially would benefit us financially than mere entertainment. This was the mind set this study tried to analyse by aiming to look at the world from the mind of a startup investor who looks at investing in products based on their intuition. In a world where time is of essence letting intuition decide might not be the optimal way ahead hence why this study aimed at solving this general problem that investors face in correspondence to today’s context and technology advancements. " | en_US |
dc.language.iso | en | en_US |
dc.subject | Startup and investment | en_US |
dc.subject | Algorithm formation | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Recommender System | en_US |
dc.title | Identify Tea Stem & Branch Diseases Found in Sri Lanka Using Image Processing | en_US |
dc.type | Thesis | en_US |