Journals & Publications

Title: Towards Human-like and Transhuman Perception in AI 2.0: A Review

Authors: Tian, YH; Chen, XL; Xiong, HK; Li, HL; Dai, LR; Chen, J; Xing, JL; Chen, J; Wu, XH; Hu, WM; Hu, Y; Huang, TJ; Gao, W

Author Full Names: Tian, Yong-hong; Chen, Xi-lin; Xiong, Hong-kai; Li, Hong-liang; Dai, Li-rong; Chen, Jing; Xing, Jun-liang; Chen, Jing; Wu, Xi-hong; Hu, Wei-min; Hu, Yu; Huang, Tie-jun; Gao, Wen

Source: FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 18 (1):58-67; 10.1631/FITEE.1601804 JAN 2017

Language: English

Abstract: Perception is the interaction interface between an intelligent system and the real world. Without sophisticated and flexible perceptual capabilities, it is impossible to create advanced artificial intelligence (AI) systems. For the next-generation AI, called 'AI 2.0', one of the most significant features will be that AI is empowered with intelligent perceptual capabilities, which can simulate human brain's mechanisms and are likely to surpass human brain in terms of performance. In this paper, we briefly review the state-of-the-art advances across different areas of perception, including visual perception, auditory perception, speech perception, and perceptual information processing and learning engines. On this basis, we envision several R&D trends in intelligent perception for the forthcoming era of AI 2.0, including: (1) human-like and transhuman active vision; (2) auditory perception and computation in an actual auditory setting; (3) speech perception and computation in a natural interaction setting; (4) autonomous learning of perceptual information; (5) large-scale perceptual information processing and learning platforms; and (6) urban omnidirectional intelligent perception and reasoning engines. We believe these research directions should be highlighted in the future plans for AI 2.0.

ISSN: 2095-9184

eISSN: 2095-9230

IDS Number: EL3TC

Unique ID: WOS:000394541200005

*Click Here to View Full Record