Biologically-inspired image interpretation and automatic target recognition technologies

被引:0
|
作者
Sheerin, D [1 ]
Doll, TJ [1 ]
Chiu, CK [1 ]
Home, R [1 ]
机构
[1] QinetiQ, Optron Technol Ctr, Malvern WR14 3PS, Worcs, England
关键词
D O I
10.1117/12.487777
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Biologically-based computer vision systems are now available that achieve robust image interpretation and automatic target recognition (ATR) performance. We describe two such systems and the reasons behind their robust performance. We also report results of three studies that demonstrate this robustness.
引用
收藏
页码:210 / 221
页数:12
相关论文
共 50 条
  • [1] A biologically-inspired concept for active image recognition
    Suri, RE
    [J]. INTERNATIONAL CONFERENCE ON INTEGRATION OF KNOWLEDGE INTENSIVE MULTI-AGENT SYSTEMS: KIMAS'03: MODELING, EXPLORATION, AND ENGINEERING, 2003, : 379 - 384
  • [2] Biologically-Inspired Target Recognition in Radar Sensor Networks
    Liang, Qilian
    [J]. WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, 2009, 5682 : 115 - 124
  • [3] A Biologically-Inspired Computational Model for Transformation Invariant Target Recognition
    Iftekharuddin, Khan M.
    Li, Yaqin
    [J]. 2008 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-8, 2008, : 1049 - 1056
  • [4] Biologically-inspired wideband target localisation
    Reich, Galen M.
    Antoniou, Michail
    Baker, Christopher J.
    [J]. IET RADAR SONAR AND NAVIGATION, 2018, 12 (12): : 1410 - 1418
  • [5] Accelerators for Biologically-Inspired Attention and Recognition
    Park, Mi Sun
    Zhang, Chuanjun
    DeBole, Michael
    Kestur, Srinidhi
    Narayanan, Vijaykrishnan
    Irwin, Mary Jane
    [J]. 2013 50TH ACM / EDAC / IEEE DESIGN AUTOMATION CONFERENCE (DAC), 2013,
  • [6] Biologically-inspired algorithms for object recognition
    Ternovskiy, I
    Nakazawa, D
    Campbell, S
    Suri, RE
    [J]. INTERNATIONAL CONFERENCE ON INTEGRATION OF KNOWLEDGE INTENSIVE MULTI-AGENT SYSTEMS: KIMAS'03: MODELING, EXPLORATION, AND ENGINEERING, 2003, : 364 - 367
  • [7] Biologically-inspired pattern recognition for odor detection
    Roppel, T
    Wilson, DM
    [J]. PATTERN RECOGNITION LETTERS, 2000, 21 (03) : 213 - 219
  • [8] BioNet: A Biologically-inspired Network for Face Recognition
    Li, Pengyu
    [J]. 2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2023, : 10344 - 10354
  • [9] Generic Object Recognition with Biologically-Inspired Features
    Gao, Changxin
    Sang, Nong
    Gao, Jun
    Zou, Lamei
    Tang, Qiling
    [J]. 2009 FOURTH INTERNATIONAL CONFERENCE ON BIO-INSPIRED COMPUTING: THEORIES AND APPLICATIONS, PROCEEDINGS, 2009, : 37 - 43
  • [10] A Biologically-inspired Attentional Approach for Face Recognition
    Khellat-Kihel, Souad
    Tistarelli, Massimo
    [J]. 2019 7TH INTERNATIONAL WORKSHOP ON BIOMETRICS AND FORENSICS (IWBF), 2019,