Deep machine learning based scene understanding
Benjamin, [4/1/2022 1:01 PM] Traditionally, the use of Artificial Intelligence is only reserved for complex industrial applications and is mostly used in niche markets. The development of Artificial Intelligence for niche applications was also expensive and time consuming. However, in the age of Ar...
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sg-ntu-dr.10356-1546942023-07-07T18:35:53Z Deep machine learning based scene understanding Wo, Benjamin Shun Xian Jiang Xudong School of Electrical and Electronic Engineering EXDJiang@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Benjamin, [4/1/2022 1:01 PM] Traditionally, the use of Artificial Intelligence is only reserved for complex industrial applications and is mostly used in niche markets. The development of Artificial Intelligence for niche applications was also expensive and time consuming. However, in the age of Artificial Intelligence, Machine Learning and the Internet of Things, such development costs have been lowered greatly and has become accessible to the masses. With the growing need for “smart” devices and applications, the field of Artificial Intelligence has also grown in popularity in recent years. The potential for Artificial Intelligence has yet to be fully tapped on, as researchers all around the world constantly work towards improving models and creating novel neural networks. Additionally, with more large corporations pushing for cutting-edge technology for commercial products, the innovation for Artificial Intelligence and Machine Learning will continue to propagate. One major field within the umbrella of Artificial Intelligence is Computer Vision, as it plays a crucial role in many applications such as self-driving transport, character recognition and facial recognition. However, Computer Vision requires intelligence to increase its effectiveness in many applications. Hence, Scene Understanding is a vital partner to Computer Vision. The combination of “Vision” and “Understanding” is a key contributor to the power of Computer Vision. Bachelor of Engineering (Electrical and Electronic Engineering) 2022-01-06T05:01:50Z 2022-01-06T05:01:50Z 2021 Final Year Project (FYP) Wo, B. S. X. (2021). Deep machine learning based scene understanding. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154694 https://hdl.handle.net/10356/154694 en A3315-202 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Wo, Benjamin Shun Xian Deep machine learning based scene understanding |
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Benjamin, [4/1/2022 1:01 PM]
Traditionally, the use of Artificial Intelligence is only reserved for complex industrial applications and is mostly used in niche markets. The development of Artificial Intelligence for niche applications was also expensive and time consuming. However, in the age of Artificial Intelligence, Machine Learning and the Internet of Things, such development costs have been lowered greatly and has become accessible to the masses. With the growing need for “smart” devices and applications, the field of Artificial Intelligence has also grown in popularity in recent years.
The potential for Artificial Intelligence has yet to be fully tapped on, as researchers all around the world constantly work towards improving models and creating novel neural networks. Additionally, with more large corporations pushing for cutting-edge technology for commercial products, the innovation for Artificial Intelligence and Machine Learning will continue to propagate.
One major field within the umbrella of Artificial Intelligence is Computer Vision, as it plays a crucial role in many applications such as self-driving transport, character recognition and facial recognition. However, Computer Vision requires intelligence to increase its effectiveness in many applications. Hence, Scene Understanding is a vital partner to Computer Vision. The combination of “Vision” and “Understanding” is a key contributor to the power of Computer Vision. |
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Jiang Xudong |
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Jiang Xudong Wo, Benjamin Shun Xian |
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Final Year Project |
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Wo, Benjamin Shun Xian |
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Wo, Benjamin Shun Xian |
title |
Deep machine learning based scene understanding |
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Deep machine learning based scene understanding |
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Deep machine learning based scene understanding |
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Deep machine learning based scene understanding |
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Deep machine learning based scene understanding |
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deep machine learning based scene understanding |
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Nanyang Technological University |
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2022 |
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https://hdl.handle.net/10356/154694 |
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