TY - CONF EP - 105 A1 - Lee, A.W.C. A1 - Yong, S.-P. UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065976128&doi=10.1109%2fSPC.2018.8704126&partnerID=40&md5=f01177ef396d7ed692126995355157ae PB - Institute of Electrical and Electronics Engineers Inc. SN - 9781538663271 Y1 - 2018/// TI - Localized Object Information from Detected Objects Based on Deep Learning in Video Scene ID - scholars10141 SP - 100 KW - Deep learning; Forecasting; Object recognition; Process control; Semantics KW - extract; feature; inference; localized; Scene understanding KW - Object detection N1 - cited By 0; Conference of 2018 IEEE Conference on Systems, Process and Control, ICSPC 2018 ; Conference Date: 14 December 2018 Through 15 December 2018; Conference Code:147803 N2 - The ultimate goal of computer vision research is to understand a scene semantically from an image or a video. Real-time object detection received significant attention over the past few years. Many challenges remain, especially in the focus of extraction of localized object information for scene representation. In order to have an accurate, intelligent and fast real-time object detection, the implementation of accurate localized information in the machine is inevitable. This research will focus on developing the object localization extractor that can extract the localized object information from the scene for further scene prediction and inference. In particular, (i) our localized extractor can encode significantly high-level features information; (ii) this rich localized information will be used for scene representation and understanding. © 2018 IEEE. AV - none ER -