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2007 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE

作者： Shao, Chenxi Fan, Jinfeng Li, Shaobin Department of Computer Science and Technology USTC Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui 230027 China Department of Computer Science and Technology USTC Hefei Anhui 230027 China

ISBN: (纸本)1424411203

Correlation dimension (CD) and the largest Lyapunov exponent (LLE), which are two most important nonlinear invariant measures of nonlinear system, are adopted to characterize the complexity and stability of human brain during all sleep stages. In order to And an optimal embedding to reconstruct phase space, the C-C method and Cao's algorithm were thoroughly analyzed and implemented in efficient ways. Additionally, the G-P algorithm and Kantz's algorithm are also implemented for calculation of CD and LLE respectively. Eight normal sleep EEG records are acquired from MIT-BIH sleep-EDF database for this study. The values of CD and LLE for 30s epochs are calculated, and their mean and standard deviation values are evaluated as well. The results indicate that CD and LLE decrease from the waking stage to stages I, II and III-IV, and they have large values during rapid eye movement (REM) sleep stage. Then, a qualitative conclusion may be drawn that during waking stage and REM sleep stage, brain activity has higher complexity and lower stability than during other stages. © 2007 IEEE.

关键词： Electroencephalography

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Multi-question negative surveys 3rd

Multi-question negative surveys

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3rd International Conference on Data Mining and Big Data, DMBD 2018 held in conjunction with the 9th International Conference on Swarm Intelligence, ICSI 2018

作者： Jiang, Hao Luo, Wenjiang Anhui Province Key Laboratory of Software Engineering in Computing and Communication School of Computer Science and Technology University of Science and Technology of China HefeiAnhui230027 China

ISBN: (纸本)9783319938028

The negative survey is an emerging method of collecting sensitive information. It could obtain the distribution of sensitive information while preserving the personal privacy. When collecting sensitive information, several questions are often provided together to the respondents. However, when reconstructing positive survey results of multiple questions, previous reconstruction methods have some shortcomings. In this paper, we propose a new reconstruction method for multi-question negative surveys. Experimental results show that our method could obtain more reasonable results. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Surveys

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A self-organized algorithm based on digital hormone

A self-organized algorithm based on digital hormone

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International Conference on Advanced computer Theory and Engineering

作者： Xia, Li Xufa, Wang Yang, Lei Haifeng, You Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424465408

In this paper, a self-organized algorithm for task allocation, based on the hormone reaction-diffusion mechanism, is proposed for a multi-robot system. Hormone messages are used to coordinate the movement of robots. By the regulation of hormones, agents could adjust their behaviors in time and improve the ability of self-organization. A simulation of task allocation in the multi-robot system is performed, experimental results demonstrate that our method can accomplish the task effectively and reduce the total cost. © 2010 IEEE.

关键词： Multipurpose robots

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A hormone-based clustering algorithm in wireless sensor networks

A hormone-based clustering algorithm in wireless sensor netw...

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2010 2nd International Conference on computer Engineering and Technology, ICCET 2010

作者： Dong, Dayuan You, Haifeng Zhang, Yipeng Wang, Xufa Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781424463503

Clustering problem is one of the hottest issues in wireless sensor networks (WSNs). The strategy for selection of cluster head has not been sufficiently investigated. In this paper, we propose a hormone-based clustering algorithm (HCA) inspired by the communication mechanism of bio-endocrine system to prolong the lifetime of the sensor nodes. Two kinds of hormones, cluster hormone and member hormone, are used in the algorithm. Hormone message can promote a node to become a cluster head or a member node. Comparative experiment shows that the proposed algorithm has effectively prolong the lifetime of WSN compared with LEACH[1] and HEED[2]. © 2010 IEEE.

关键词： Clustering algorithms

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Mac address assignment in wireless sensor networks: A mixed strategy game approach

Mac address assignment in wireless sensor networks: A mixed ...

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2nd International Conference on Systems and Networks communications, ICSNC 2006

作者： Kun, Tu Kun, Bi Naijie, Gu Wanli, Dong Xiaohu, Liu Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui 230027 China

ISBN: (纸本)0769526993

In this paper, we address the problem of MAC address assignment in wireless sensor networks. A novel scheme for MAC address assignment is proposed to reduce the overhead. We model the problem from the game theoretical view, prove there exists a mixed strategy Nash equilibrium in the model, and propose a distributed address assign algorithm to achieve the equilibrium, which takes the advantage of the exploitation of spatial address reuse to save energy. Simulation results demonstrate that our algorithm is efficient even for very large-scale networks, which makes it a potential candidate for practical applications. © IEEE.

关键词： Medium access control

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Topological hole detection in sensor networks with cooperative neighbors

Topological hole detection in sensor networks with cooperati...

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2nd International Conference on Systems and Networks communications, ICSNC 2006

作者： Kun, Bi Kun, Tu Naijie, Gu Wanli, Dong Xiaohu, Liu Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui 230027 China

ISBN: (纸本)0769526993

In a wireless sensor network, the regions in which a large percentage of sensor nodes are not available may form holes in the network. In holes, sensor nodes may be depleted or not dense enough to communicate with others. So those holes may degrade some applications' performances in sensor networks. In this paper, we study the problem of detecting topological holes in sensor networks with no localization information in any node. We present a distributed cooperative scheme which is only based on the communication topology graph. To identify holes, each node only needs to exchange information with its 1-hop and 2-hop neighbors. With the cooperation of its 2-hop neighbors, each node could independently decide whether it is on the boundary of a hole. Experimental results demonstrate that our algorithm could indeed capture the characteristics of those boundary nodes and describe those holes in sensor networks of moderate node densities. © IEEE.

关键词： Wireless sensor networks

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Emotion recognition from thermal infrared images using deep Boltzmann machine

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Frontiers of computer Science 2014年第4期8卷 609-618页

作者： Shangfei WANG Menghua HE Zhen GAO Shan HE Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA

Facial expression and emotion recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there are no image features specially designed for thermal infrared images. In this paper, we propose using the deep Boltzmann machine to learn thermal features for emotion recognition from thermal infrared facial images. First, the face is located and normalized from the thermal infrared im- ages. Then, a deep Boltzmann machine model composed of two layers is trained. The parameters of the deep Boltzmann machine model are further fine-tuned for emotion recognition after pre-tralning of feature learning. Comparative experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, eye, and mouth are more effective for discriminating valence dimension of emotion than other facial areas. In addition, our study shows that adding unlabeled data from other database during training can also improve feature learning performance.

关键词： emotion recognition thermal infrared images deep Boltzmann machine

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Unpaired Multimodal Facial Expression Recognition 15th

Unpaired Multimodal Facial Expression Recognition

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15th Asian Conference on computer Vision, ACCV 2020

作者： Xia, Bin Wang, Shangfei Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China Anhui Robot Technology Standard Innovation Base Hefei China

ISBN: (纸本)9783030695408

Current works on multimodal facial expression recognition typically require paired visible and thermal facial images. Although visible cameras are readily available in our daily life, thermal cameras are expensive and less prevalent. It is costly to collect a large quantity of synchronous visible and thermal facial images. To tackle this paired training data bottleneck, we propose an unpaired multimodal facial expression recognition method, which makes full use of the massive number of unpaired visible and thermal images by utilizing thermal images to construct better image representations and classifiers for visible images during training. Specifically, two deep neural networks are trained from visible and thermal images to learn image representations and expression classifiers for two modalities. Then, an adversarial strategy is adopted to force statistical similarity between the learned visible and thermal representations, and to minimize the distribution mismatch between the predictions of the visible and thermal images. Through adversarial learning, the proposed method leverages thermal images to construct better image representations and classifiers for visible images during training, without the requirement of paired data. A decoder network is built upon the visible hidden features in order to preserve some inherent features of the visible view. We also take the variability of the different images’ transferability into account via adaptive classification loss. During testing, only visible images are required and the visible network is used. Thus, the proposed method is appropriate for real-world scenarios, since thermal imaging is rare in these instances. Experiments on two benchmark multimodal expression databases and three visible facial expression databases demonstrate the superiority of the proposed method compared to state-of-the-art methods. © 2021, Springer Nature Switzerland AG.

关键词： Infrared imaging

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A spontaneous facial expression recognition method using head motion and AAM features

A spontaneous facial expression recognition method using hea...

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2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010

作者： Lv, Yanpeng Wang, Shangfei Key Lab of Computing and Communicating Software of AnHui Province School of Computer Science and Technology University of Science and Technology of China HeFei AnHui China

ISBN: (纸本)9781424473762

Facial expression recognition by artificial intelligence has become a hotspot and produced promising results in recent years. However, most recent work focuses on posed expressions whose involved muscles and dynamics are different from those of spontaneous ones. So this paper proposed a novel two-layer approach, combining dynamic head motion features with static appearance features, to recognize spontaneous expressions. Different from other methods, our method improved an existing eyes location algorithm and explored new head motion features calculated from locations of pupils to recognize fear firstly, and then used appearance features extracted by the AAM algorithm to recognize the remaining images. Comparative experiments on the natural visible and infrared facial expression database (NVIE) show the effectiveness of our approach. © 2010 IEEE.

关键词： Location

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Spontaneous facial expression recognition based on feature point tracking

Spontaneous facial expression recognition based on feature p...

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International Conference on Image and Graphics

作者： He, Shan Wang, Shangfei Lv, Yanpeng Key Lab of Computing and Communicating Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9780769545417

In recent years, facial expression recognition has attracted a lot of attention because of its importance in human-computer interaction. However, most previous work has focus on posed expression. In this paper, we propose a spontaneous facial expression recognition method based on feature point tracking. First, all expression sequences are normalized according to their pupils' coordinates. Second, 23 points are labeled manually in the onset and apex frames. Then Kalman filter is used for tracking. Two kinds of features, point displacement features and points distance variation features, are extracted. Finally, Hidden Markov Model is employed as classifier. Experiments have been conducted on the spontaneous facial expression database of USTC-NVIE. The results indicate that Kalman filter point tracking method could detect the right place of points, and the points distance variation features are more suitable than the point displacement features for the facial expression recognition. © 2011 IEEE.

关键词： Kalman filters

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