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401.
之前的相关研究表明相位锁定的脑电活动调节自我相关物主代词的认知加工。然而,非相位锁定的神经震荡是否参与自我相关物主代词的加工目前还不清楚。为了考察非相位锁定的神经震荡在自我相关物主代词加工中的功能性意义,我们要求被试完成一个标准/偏差刺激辨别任务,同时记录其脑电活动。小波分析的结果发现相对于非自我相关物主代词“他的”,自我相关物主代词“我的”引发了更大的 theta 频带(4~8 Hz)能量活动,这表明 theta 波的活动对自我相关信息加工中脑的大范围神经同步形成的功能性神经网络起着一个很重要的作用。 相似文献
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抑郁逐渐低龄化使得青少年抑郁备受关注。快感缺失,作为抑郁的一种核心临床症状,已成为抑郁最具前景的内表型之一。然而,青少年抑郁的快感缺失的神经机制迄今仍不清楚。本研究首先汇总两种神经机制模型即三元模型和社会挫折模型;其次,在多种奖励加工如金钱奖励、努力动机奖励、未来奖励和社会奖励条件下,概述青少年抑郁的快感缺失的神经机制前沿进展。未来可以深入探索努力动机奖励和未来奖励在预测青少年抑郁中的作用,加强研究青春期阶段与性别是如何交互影响早期抑郁快感缺失,将无创伤电磁刺激应用于青少年抑郁干预中,进一步澄清青少年抑郁的快感缺失的神经发展机制。 相似文献
405.
Application of artificial intelligence in Bio-Medical image processing is gaining more and more importance in the field of Medical Science. The bio medical images, has to go through several steps before the diagnosis of the disease. Firstly, the images has to be acquired and preprocessing has to be done and the data has to be stored in memory. It requires huge amount of memory and processing time. Among the preprocessing steps, edge detection is one of the major step. Edge detection filters the unwanted details in the image, and preserves the edges of the image, which describe the boundary of the image. In biomedical application, for the detection of the diseases, it is very essential to have the boundary detail of the acquired image of the organ under observation. Thus it is very essential to extract the edges of the images. Power is one of the main parameters that have to be considered while dealing with biomedical instruments. The biomedical signal processing instruments should be capable of operating at low power and also at high speed. In order to segregate the images into different levels or stage, we use convolutional neural networks for classification. By having a hardware architecture for image edge detection, the computational time for pre-processing of the image can be reduced, and the hardware can be a part of acquisition device itself. In this paper a low-power architecture for edge detection to detect the biomedical images are presented. The edge detection output are given to the system, which will diagnose the diseases using image classification using convolutional neural network. In this paper, Sobel and Prewitt, algorithms are used for edge detection using 180 nm technology. The edge detection algorithms are implemented using VLSI, and digital IC design of the architecture is presented. The algorithms for edge detection is co-simulated using MATLAB and Modelsim. The architecture is first simulated using CMOS logic and new method using domino logic is presented for low power consumption. 相似文献
406.
Facial expression recognition in a wild situation is a challenging problem in computer vision research due to different circumstances, such as pose dissimilarity, age, lighting conditions, occlusions, etc. Numerous methods, such as point tracking, piecewise affine transformation, compact Euclidean space, modified local directional pattern, and dictionary-based component separation have been applied to solve this problem. In this paper, we have proposed a deep learning–based automatic wild facial expression recognition system where we have implemented an incremental active learning framework using the VGG16 model developed by the Visual Geometry Group. We have gathered a large amount of unlabeled facial expression data from Intelligent Technology Lab (ITLab) members at Inha University, Republic of Korea, to train our incremental active learning framework. We have collected these data under five different lighting conditions: good lighting, average lighting, close to the camera, far from the camera, and natural lighting and with seven facial expressions: happy, disgusted, sad, angry, surprised, fear, and neutral. Our facial recognition framework has been adapted from a multi-task cascaded convolutional network detector. Repeating the entire process helps obtain better performance. Our experimental results have demonstrated that incremental active learning improves the starting baseline accuracy from 63% to average 88% on ITLab dataset on wild environment. We also present extensive results on face expression benchmark such as Extended Cohn-Kanade Dataset, as well as ITLab face dataset captured in wild environment and obtained better performance than state-of-the-art approaches. 相似文献
407.
This article first introduced the current technology of the privacy protection model, and analyzed their characteristics and deficiencies. Afterwards, from the point of view of revenue, the shortcomings of the traditional privacy protection model have analyzed through the group intelligent computing method. Based on this, this paper proposes a research and application of virtual user information of security strategy based on group intelligent computing, through the collection of visitor's private information historical access data, intelligent calculation of the strategy group between the visitor and the interviewee. The setting of the threshold of the visited person can protect the privacy information of the user more effectively. In this paper, the implementation flow, algorithm implementation process, and specific architecture design of the proposed virtual user of privacy protection model based on group intelligent computing are introduced respectively. The specific algorithms include PCA, BP neural network, and genetic algorithm. Finally, the proposed privacy has verified through experiments. Protection model can protect user privacy more effectively than traditional privacy protection model. In the future, we will further expand and improve the privacy protection model of virtual users based on group intelligent computing, including considering the dynamic and inconsistency of access to the privacy information, that is, accessing different private information will produce different overlay effects and parallelism. We will also study how to apply this model to actual systems such as shopping websites and social platforms, and use commercial data to evaluate the performance of the model and further improve it. 相似文献
408.
近年来,许多研究者开始关注社会交流中的人际神经同步机制,并将人际神经同步作为研究社会交流的一个神经指标,这对于揭示社会交流的本质和规律具有重要意义。本文从心理理论和镜像神经系统的角度,分析社会交流中神经同步的认知机制及其影响因素。未来的研究应关注这两套机制是否因交流目的、对象、形式或内容的不同,而在不同的脑区表现出神经同步,进而引发了不同认知机制的争议;以及这两套机制各自或协同工作适用的情景和任务。 相似文献
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