一种权值可发育的视觉选择性注意模型研究Research on a visual selective attention model with weight development
李福进,杜建,任红格,史涛
摘要(Abstract)：
针对Itti视觉选择性注意模型不具有子特征图显著图归一化过程中权值随任务改变而改变的问题,借鉴自主发育在视觉选择性注意学习的研究成果,提出一种权值可发育视觉选择性注意模型作为图像特征提取的学习机制。该算法采用三层自组织神经网络和Itti视觉选择性注意模型相结合的决策进行寻优,通过对模型的训练学习获取最优权值更新。这样既可以保证在初期特征提取内容的完整性,又降低了系统对不同任务条件的约束性,提高了模型特征提取能力。利用权值可发育视觉选择性注意模型对图像进行感兴趣区域特征提取实验,结果表明,该方法能够提高特征提取准确性、减少运算时间,获得了良好的动态性能。
关键词(KeyWords)： Itti视觉选择性注意模型;权值可发育;自主发育;特征提取;显著图;模型训练
基金项目(Foundation): 国家自然科学基金项目(61203343);; 河北省自然科学基金项目(E2014209106);; 河北省教育厅高等学校科学技术研究项目(QN2016102);河北省教育厅高等学校科学技术研究项目(QN2016105)~~
作者(Author): 李福进,杜建,任红格,史涛
DOI: 10.16652/j.issn.1004-373x.2018.10.047
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