Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77715
Title: Harnessing object detection for learning
Authors: Yap, Jinson
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2019
Abstract: The current rapid development of technology and applications of object detection has always been an important Image recognition is a research area that is ongoing and is always challenging to task it in computer vision in many areas. There is a large array of different object categories, hence we need to train. Object recognition for new object in datasets requires more time to process to those classifiers, as it needs to be trained to allow the database to increase. However, there are existing file that have datasets like TensorFlow. This project proposed to use this content to implement on app to enhance the children’s education through technology. Education is key to development in kids learning ability and with this project it will enhance the kids learning. This project labels each individual elements of an image into its own category regions and provide a label for each object. The of methods extracting features from an annotated image are store into database containing about 100000 images and 200 objects. Every parameter has its own futures that can be explored, and analysed to achieved the best accuracy.
URI: http://hdl.handle.net/10356/77715
Schools: School of Electrical and Electronic Engineering 
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Final Yap Jinson ( DONE ).pdf
  Restricted Access
2.25 MBAdobe PDFView/Open

Page view(s)

285
Updated on Oct 9, 2024

Download(s)

11
Updated on Oct 9, 2024

Google ScholarTM

Check

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