Please use this identifier to cite or link to this item:
Title: Deep machine learning based scene understanding
Authors: Wo, Benjamin Shun Xian
Keywords: Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Wo, B. S. X. (2021). Deep machine learning based scene understanding. Final Year Project (FYP), Nanyang Technological University, Singapore.
Project: A3315-202
Abstract: 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.
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
1.83 MBAdobe PDFView/Open

Page view(s)

Updated on Jun 29, 2022

Download(s) 20

Updated on Jun 29, 2022

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.