CASIA OpenIR  > 毕业生  > 硕士学位论文
Thesis Advisor曾毅
Degree Grantor中国科学院研究生院
Place of Conferral北京
Keyword初级视皮层 腹侧通路 类脑轮廓提取算法 分层时序记忆模型
其次,本文研究了大脑皮层机理的分层时序记忆模型(Hierarchical Temporal Memory,HTM),并基于HTM模型进行腹侧通路计算模型的构建,使其更符合视皮层的生物学特性,本文将其应用于手写体和“幻视”图片识别的任务中,取得了较好的效果。同时,HTM在“幻视”图片识别任务中的结果比卷积神经网络LeNet-5的结果更好,这也间接表明了HTM更符合人脑的视觉机制。
Other Abstract
Vision, as one of the most important perceptual modes of human beings, is one of the main ways for human to obtain information. About 70% of the information in human brain comes from the eyes, and probably 20%-30% cortex area is used for visual processing. In the long process of evolution, human visual system has become one of the information processing systems with complete function and perfect mechanism, which implies many highly efficient visual image processing mechanisms.
As a "rough" brain-like model of computation, deep learning requires a large number of training samples. The human visual learning process is based on small-sample, which fully embodies the flexibility and efficiency of human vision. In addition, compared with the computer vision, the human visual processing process is very fast and robust. Therefore, the research on the processing mechanism of visual information is not only helpful to understand the working mechanisms of the brain, but to improve the efficiency and performance of the computer vision.
The development of neural anatomy and neuroimaging provides a rich physiological basis for simulating the structure and mechanism of visual cortex as well as constructing the computational model of visual system. In this paper, the structures and mechanisms of the primary visual system and ventral pathway as well as the related visual computing model are fully investigated, the main works include:
Firstly, base on MCI model which is a biological vision mechanisms inspired model, we proposed sMCI and sCMCI models, which integrate with some more psychological phenomena and biological mechanisms of primary visual cortex. Therefore, they are more brain-inspired. This paper validates the models on unmanned aerial vehicle data being collected by our laboratory as well as some public datasets, and the results show that the proposed models can accelerate the speed and keep the performance of the contour detection.
Secondly, based on the hierarchical temporal memory model (HTM), this paper constructs the computational model of the ventral pathway. Based on the existing sMCI model and the connection and weight of the ventral pathway, the HTM model is improved to accord with the biological characteristics of the visual cortex. We apply it to the tasks of handwritten character recognition and illusion recognition and obtain some good results. And illusion recognition performance of HTM outperforms the result of convolutional neural network LeNet-5, which indirectly illustrates that the HTM is more conform to the mechanism of human brain.
Document Type学位论文
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
康晓梅. 受皮层结构与机制启发的视觉腹侧通路建模与应用[D]. 北京. 中国科学院研究生院,2018.
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