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Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 5, Pages 738-750 doi: 10.1631/FITEE.1500380
Keywords： Speaker recognition Histogram equalization i-vector
Latent discriminative representation learning for speaker recognition Research Articles
Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routryar, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.1900690
Keywords： 说话人识别；潜在可区分性表征学习；说话人嵌入查找表；线性映射矩阵
A new score normalizaion algorithm based on EMD-Tnorm for speaker verification
Li Yanping,Ding Hui,Tang Zhenmin
Strategic Study of CAE 2010, Volume 12, Issue 2, Pages 95-100
In this paper, the verification system from two aspects was improved. On one hand, we extended MixMax model that the EMD (earth mover's distance) can be applied, which can remove the disturbance of noise; on the other hand, we improved the Tnorm score normalization method based on the EMD. Experimental results show that this method can compensate the speaker-dependent and test-dependent variability, also show a stable performance improvement by decreasing the FA and FR.
Keywords： speaker verification robustness earth mover’s distance MixMax model
Man-machine verification of mouse trajectory based on the random forestmodel Research Articles
Zhen-yi XU, Yu KANG, Yang CAO, Yu-xiao YANG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 7, Pages 925-929 doi: 10.1631/FITEE.1700442
Identifying code has been widely used in man-machine verification to maintain network security. The challenge in engaging man-machine verification involves the correct classification of man and machine tracks. In this study, we propose a random forest (RF) model for man-machine verification based on the mouse movement trajectory dataset. We also compare the RF model with the baseline models (logistic regression and support vector machine) based on performance metrics such as precision, recall, false positive rates, false negative rates, F-measure, and weighted accuracy. The performance metrics of the RF model exceed those of the baseline models.
Keywords： Man-machine verification Random forest Support vector machine Logistic regression Performance metrics
Lin Heng,Zhou Yuan and Liu Yufei
Strategic Study of CAE 2017, Volume 19, Issue 1, Pages 124-132 doi: 10.15302/J-SSCAE-2017.01.018
This paper focuses on technology hot spots, frontier identification, and trend analysis of high-tech foresight, and puts forward a more complete analysis method based on previous studies. In this paper, we take robot technology as an example in order to identify hot spots and frontiers in technology, along with their development trends. These findings have great significance for the proposal of a technology list and for the allocation of the technology industry in the Research on China’s Engineering Science and Technology Development Strategy 2035.
Keywords： technology foresight technology hot spots frontier of technology patent analysis robot technology
Brain–Computer Interface Speaks up
Chris Palmer
Engineering 2022, Volume 9, Issue 2, Pages 3-5 doi: 10.1016/j.eng.2021.12.004
Autonomous flying blimp interaction with human inan indoor space None
Ning-shi YAO, Qiu-yang TAO, Wei-yu LIU, Zhen LIU, Ye TIAN, Pei-yu WANG, Timothy LI, Fumin ZHANG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 1, Pages 45-59 doi: 10.1631/FITEE.1800587
We present the Georgia Tech Miniature Autonomous Blimp (GT-MAB), which is designed to support human-robot interaction experiments in an indoor space for up to two hours. GT-MAB is safe while flying in close proximity to humans. It is able to detect the face of a human subject, follow the human, and recognize hand gestures. GT-MAB employs a deep neural network based on the single shot multibox detector to jointly detect a human user’s face and hands in a real-time video stream collected by the onboard camera. A human-robot interaction procedure is designed and tested with various human users. The learning algorithms recognize two hand waving gestures. The human user does not need to wear any additional tracking device when interacting with the flying blimp. Vision-based feedback controllers are designed to control the blimp to follow the human and fly in one of two distinguishable patterns in response to each of the two hand gestures. The blimp communicates its intentions to the human user by displaying visual symbols. The collected experimental data show that the visual feedback from the blimp in reaction to the human user significantly improves the interactive experience between blimp and human. The demonstrated success of this procedure indicates that GT-MAB could serve as a flying robot that is able to collect human data safely in an indoor environment.
Keywords： Robotic blimp Human-robot interaction Deep learning Face detection Gesture recognition
一种易用的实体识别消歧系统评测框架 Article
辉 陈,宝刚 魏,一鸣 李,Yong-huai LIU,文浩 朱
Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 2, Pages 195-205 doi: 10.1631/FITEE.1500473
Keywords： 实体识别消歧；评测框架；信息抽取
A partition approach for robust gait recognition based on gait template fusion Research Articles
Kejun Wang, Liangliang Liu, Xinnan Ding, Kaiqiang Yu, Gang Hu,heukejun@126.com,liuliangliang@hrbeu.edu.cn,dingxinnan@hrbeu.edu.cn,yukaiqiang@hrbeu.edu.cn,hugang@hrbeu.edu.cn
Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5, Pages 615-766 doi: 10.1631/FITEE.2000377
Surface Ship Target Recognition Research Based on SGA
Jiang Dingding,Xu Zhaolin,Li Kairui
Strategic Study of CAE 2004, Volume 6, Issue 8, Pages 79-81
Surface ship recognition is an important contents of navy's aviation probe. This text discussed the principle, characteristics and calculating step of SGA, and applied this calculating way to surface ship recognition. The experiment results proved the scientificalness and the practical applicability of that methoded.
Keywords： SGA target recognition surface ship
Application of RFID in the Visual Logistics System
Wang Aiming,Mu Xiaoxi,Li Aihua
Strategic Study of CAE 2006, Volume 8, Issue 8, Pages 65-68
The radio frequency identification (RFID) is a kind of new automatic identification technology. It has many characteristics such as high reliability, privacy , non-contact, convenient and swift. Applying RFID to visual logistics system, can gain actual requirement of guaranteed object and information about the type, amount and way of materials to supply and ensure the supply in the whole time, orientation and course. The paper introduces the RFID system and its principle, and brings about an application of RFID in visual logistics system, which is realized by the radio frequency labels stuck to the containers and equipments.
Keywords： visual logistics radio frequency identification visual system for the carrying materials
Pattern Recognition With Fuzzy Central Clustering Algorithms
Zen Huanglin,Yuan Hui,Liu Xiaofang
Strategic Study of CAE 2004, Volume 6, Issue 11, Pages 33-37
Based on optimization of constrained nonlinear programming, an approach of clustering center and a fuzzy membership function of pattern classification are derived from an objective function of the constrained nonlinear programming. An unsupervised algorithm with recursive expression and a fuzzy central cluster neural network are suggested in this paper. The fuzzy central cluster neural network proposed here can realize crisp decision or fuzzy decision in pattern classification.
Keywords： fuzzy sets central cluster pattern recognition neural network
From Remotely Operated Vehicles to Autonomous Undersea Vehicles
Feng Xisheng
Strategic Study of CAE 2000, Volume 2, Issue 12, Pages 29-33
A clear definition and a very fine classification of the unmanned undersea vehicles are given in this paper. Following a brief introduction of the advances on the unmanned undersea vehicles the paper points out that the autonomous underwater vehicles at present is a hot spot in the research realm of the unmanned undersea vehicles. This paper describes the research and development achievements pertinent to the unmanned undersea vehicles in Shenyang Institute of Automation (SIA), Chinese Academy of Sciences with the cooperation of organizations home and abroad in the last two decades. SIA started to be engaged in the research and development of the remotely operated tethered vehicles in the end of 1970's. This paper gives a wide introduction of the critical characteristics and technical descriptions of the first remotely operated tethered vehicle “HR- 01” in China, the first autonomous underwater vehicle “Explorer” and the autonomous underwater vehicle CR-01 (6 000 m).
Keywords： undersea vehicles ROV AUV ocean engineer ocean resources exploration
Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks
Lu Shuang,Zhang Zida,Li Meng
Strategic Study of CAE 2004, Volume 6, Issue 2, Pages 56-60
Radial basis function neural network is a type of three — layer feedforward network. It has many good properties, such as powerful ability for function approximation, classification and learning rapidly. In this paper, in the light of the merit of radial basis function neural network and on the basis of the feature analysis of vibration signal of rolling bearing, AR model is presented by using time series method. Radial basis function neural networks is established based on AR model parameters. In the light of the theory of radial basis function neural networks, fault pattern of rolling bearing is recognized correspondingly. Theory and experiment show that the recognition of fault pattern of rolling bearing based on radial basis function neural networks theory is available and its precision is high.
Keywords： rolling bearing vibration signal AR model RBF neural networks pattern recognition
Binary neural networks for speech recognition Regular Papers
Yan-min QIAN, Xu XIANG
Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 5, Pages 701-715 doi: 10.1631/FITEE.1800469
Recently, deep neural networks (DNNs) significantly outperform Gaussian mixture models in acoustic modeling for speech recognition. However, the substantial increase in computational load during the inference stage makes deep models difficult to directly deploy on low-power embedded devices. To alleviate this issue, structure sparseness and low precision fixed-point quantization have been applied widely. In this work, binary neural networks for speech recognition are developed to reduce the computational cost during the inference stage. A fast implementation of binary matrix multiplication is introduced. On modern central processing unit (CPU) and graphics processing unit (GPU) architectures, a 5–7 times speedup compared with full precision floatingpoint matrix multiplication can be achieved in real applications. Several kinds of binary neural networks and related model optimization algorithms are developed for large vocabulary continuous speech recognition acoustic modeling. In addition, to improve the accuracy of binary models, knowledge distillation from the normal full precision floating-point model to the compressed binary model is explored. Experiments on the standard Switchboard speech recognition task show that the proposed binary neural networks can deliver 3–4 times speedup over the normal full precision deep models. With the knowledge distillation from the normal floating-point models, the binary DNNs or binary convolutional neural networks (CNNs) can restrict the word error rate (WER) degradation to within 15.0%, compared to the normal full precision floating-point DNNs or CNNs, respectively. Particularly for the binary CNN with binarization only on the convolutional layers, the WER degradation is very small and is almost negligible with the proposed approach.
Keywords： Speech recognition Binary neural networks Binary matrix multiplication Knowledge distillation Population count
Title Author Date Type Operation
Histogram equalization using a reduced feature set of background speakers’ utterances for speaker recognition
Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU
Journal Article
Latent discriminative representation learning for speaker recognition
Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routryar, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn
Journal Article
A new score normalizaion algorithm based on EMD-Tnorm for speaker verification
Li Yanping,Ding Hui,Tang Zhenmin
Journal Article
Man-machine verification of mouse trajectory based on the random forestmodel
Zhen-yi XU, Yu KANG, Yang CAO, Yu-xiao YANG
Journal Article
Technology Hot Spots and Frontier Identification Support to 2035: The Technology List Adjustment Method, Using Robot Technology as an Example
Lin Heng,Zhou Yuan and Liu Yufei
Journal Article
Autonomous flying blimp interaction with human inan indoor space
Ning-shi YAO, Qiu-yang TAO, Wei-yu LIU, Zhen LIU, Ye TIAN, Pei-yu WANG, Timothy LI, Fumin ZHANG
Journal Article
A partition approach for robust gait recognition based on gait template fusion
Kejun Wang, Liangliang Liu, Xinnan Ding, Kaiqiang Yu, Gang Hu,heukejun@126.com,liuliangliang@hrbeu.edu.cn,dingxinnan@hrbeu.edu.cn,yukaiqiang@hrbeu.edu.cn,hugang@hrbeu.edu.cn
Journal Article
Surface Ship Target Recognition Research Based on SGA
Jiang Dingding,Xu Zhaolin,Li Kairui
Journal Article
Pattern Recognition With Fuzzy Central Clustering Algorithms
Zen Huanglin,Yuan Hui,Liu Xiaofang
Journal Article
Fault Pattern Recognition of Rolling Bearing Based on Radial Basis Function Neural Networks
Lu Shuang,Zhang Zida,Li Meng
Journal Article
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