Improving classification of neural networks by reducing lens aperture

被引：0
|
作者：
Stainvas, I [1 ]
Zalevsky, Z [1 ]
Mendlovic, D [1 ]
Intrator, N [1 ]
机构：
[1] Tel Aviv Univ, Sch Comp Sci, IL-69978 Tel Aviv, Israel
来源：
APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION V | 2002年 / 4787卷
关键词：
classification network; face recognition; network ensembles; image blur; lens aperture; artificial neural networks; hybrid architecture;
D O I：
10.1117/12.453545
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Image blur strongly degrades object recognition. We propose a mechanism to reduce defocus blur by reducing the aperture of the camera lens, and show that it leads to a far more robust recognition. The recognition is demonstrated via a Neural Network architecture that we have previously proposed for blurred face recognition.
引用
收藏
页码：267 / 276
页数：10
相关论文
共 50 条
  • [21] Improving land-cover classification using recognition threshold neural networks
    Aitkenhead, M. J.
    Dyer, R.
    PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2007, 73 (04): : 413 - 421
  • [22] Improving brain tumor classification with combined convolutional neural networks and transfer learning
    Incir, Ramazan
    Bozkurt, Ferhat
    KNOWLEDGE-BASED SYSTEMS, 2024, 299
  • [23] Improving the classification accuracy of RBF and MLP neural networks trained with imbalanced samples
    Alejo, R.
    Garcia, V.
    Sotoca, J. M.
    Mollineda, R. A.
    Sanchez, J. S.
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2006, PROCEEDINGS, 2006, 4224 : 464 - 471
  • [24] A Novel Strategy for Improving the Counter Propagation Artificial Neural Networks in Classification Tasks
    Belattar, Sara
    Abdoun, Otman
    Haimoudi, El Khatir
    JOURNAL OF COMMUNICATIONS SOFTWARE AND SYSTEMS, 2022, 18 (01) : 17 - 27
  • [25] A Guided Method for Improving the Video Human Action Classification in Convolutional Neural Networks
    Mao L.
    Chen S.
    Yang D.
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2021, 46 (08): : 1241 - 1246
  • [26] Improving wetland cover classification using artificial neural networks with ensemble techniques
    Hu, Xudong
    Zhang, Penglin
    Zhang, Qi
    Wang, Junqiang
    GISCIENCE & REMOTE SENSING, 2021, 58 (04) : 603 - 623
  • [27] Improving Error Related Potential Classification by using Generative Adversarial Networks and Deep Convolutional Neural Networks
    Gao, Chenguang
    Li, Zhao
    Ora, Hiroki
    Miyake, Yoshihiro
    2020 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE, 2020, : 2468 - 2476
  • [28] Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide-field Small Aperture Telescopes
    Jia, Peng
    Liu, Qiang
    Sun, Yongyang
    ASTRONOMICAL JOURNAL, 2020, 159 (05):
  • [29] Graph Relearn Network: Reducing performance variance and improving prediction accuracy of graph neural networks
    Huang, Zhenhua
    Li, Kunhao
    Jiang, Yihang
    Jia, Zhaohong
    Lv, Linyuan
    Ma, Yunjie
    KNOWLEDGE-BASED SYSTEMS, 2024, 301
  • [30] Improving prognosis and reducing decision regret for pancreatic cancer treatment using artificial neural networks
    Walczak, Steven
    Velanovich, Vic
    DECISION SUPPORT SYSTEMS, 2018, 106 : 110 - 118
12345