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IEEE Workshop on Multimedia Signal processing

作者： Wei Lei Ruiqin Xiong Siwei Ma Luhong Liang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences (CAS) Beijing China Institute of Digital Media Peking University Beijing China

In image/video processing software and hardware products, low complexity interpolation algorithms, such as cubic and splines methods, are commonly used. However, these methods tend to blur textures and produce jaggy effect compared with other adaptive methods such as NEDI, SAI. Tanner graph based image interpolation algorithm has better effect in dealing with edge and texture, but with high computation complexity. Thanks to the high performance parallel processing capability of today's GPU, use of complex algorithms for real time application is becoming possible. In this paper, we present a fast algorithm for tanner graph based image interpolation and it's implementation on GPU. In our algorithm, the image model training process of tanner graph based image interpolation is greatly simplified. Experimental results show that the GPU implementation can be more than 47 times as fast as the CPU implementation.

关键词： Graphics processing unit Interpolation Training Instruction sets Parallel processing Equations Image resolution

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An algebraic multi-class classification method

An algebraic multi-class classification method

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Qing He Zhen-Yan Liu Zhong-Zhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Software Beijing Institute of Tèchnology Beijing China

ISBN: (纸本)0780384032

An algebraic multi-class classification method AHSC, i.e., algebraic hyper surface classification, is proposed. The separating algebraic hyper surface of two-class data may be directly constructed by a single polynomial in theory, but it is too difficult to separate multi-class data by a single polynomial even though the polynomial is multivalued. AHSC can be used for classifying multi-class data by integrating a series of polynomial networks based on binary numbers, which are used for labeling the classes of samples. The problem that multi-class data cannot always be separated by a single polynomial is solved by AHSC. Moreover, using an adaptive method can choose the order of polynomial. The experimental results show that the new method can efficiently and accurately classify multi-class and high dimension data.

关键词： Polynomials Machine learning Error correction codes Mathematical model Neurons Vectors Helium information processing Computers Electronic mail

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A feature selection algorithm based on tolerant granule

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Journal of Convergence information Technology 2011年第1期6卷 191-195页

作者： Ding, Shifei Zhang, Yu Xu, Li Qian, Jun School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

The bottleneck problem has emerged in feature selection when processing high-dimension and large-scale data, so in the past decade, the researches on feature selection have not adhere to the traditional algorithms and ideas, showing a new trend of combining many new mathematical tools, which opens new space for feature selection applied in pattern recognition and makes further development in knowledge discovery and data mining. Granular computing has begun to take shape and show effect as a new idea of intelligent information processing, which creates the conditions for feature selection applied in data. The paper describes a new feature selection algorithm, basing on granular computing and making rough set approximation as background, the algorithm generates the granules, using a tolerance function, distinguishes noise data and inconsistent data, to achieve feature selection in the information table, and be effective for large-scale data sets.

关键词： Feature Selection

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Ultra-wideband MIMO Antenna Design Based on EBG Structure

Ultra-wideband MIMO Antenna Design Based on EBG Structure

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Zhipeng Chen Shijie Huang Zhongxiang Zhang Xianliang Wu Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Heifei China Anhui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Heifei China

ISBN: (纸本)9781665409889

This paper proposes a low-coupling planar compact four-element ultra-wideband antenna based on the EBG structure for multiple-input multiple-output (MIMO) systems. The MIMO antenna is composed of four miniaturized monopole antenna elements based on the half-cut method and a periodic electromagnetic band gap (EBG) structure. The traditional mushroom-shaped EBG structure is cut into squares and a pair of harpoon-shaped microstrip lines are introduced. Structure to reduce its resonant frequency and increase the band gap width. By loading the improved EBG structure in the middle of the MIMO antenna, the electromagnetic coupling between the components is greatly reduced. In addition, the stop band characteristics in the WLAN band (5.725–5.825GHz) are realized by adding a U-shaped resonant stub to the right side of the feeder of the monopole antenna. The experimental results show that it has a good reflection coefficient in the passband bandwidth range of 2.90–11.7GHz, covering the 3.1–10.6GHz frequency band specified by UWB, the isolation between the components is greater than 15dB, and good envelope correlation. The coefficient ECC is <0.02, which proves that the antenna is a potential candidate for ultra-wideband applications.

关键词： Correlation Resonant frequency Bandwidth Metamaterials Ultra wideband antennas Reflection coefficient Passband

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Text Document Clustering and the Space of Concept on Text Document Automatically Generated

Text Document Clustering and the Space of Concept on Text Do...

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2001 International Conferences on Info-tech and Info-net

作者： Fu Weipeng Wu Bin He Qing Shi Zhongzhi Graduate school of University of Science and Technology of China The Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

A method of automatically generated to the space of the concept on text document is ***, cluster the text document through SOM and gain the concept of text for mark the classification,and then using the fuzzy clustering to automatically generate and sum up the concept space for managing the text *** result can be used to cluster the Chinese document and generates an index of the cluster *** is an unsupervised-learning neural-network method that produces a mapping from text space into concept *** experiments and test results are shown that the space of concept does well in arranging the classification of the text and is convenient to information retrieval.

关键词： concept space text index Self-Organizing Maps

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ES3: Evolving Self-Supervised Learning of Robust Audio-Visual Speech Representations

ES3: Evolving Self-Supervised Learning of Robust Audio-Visua...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yuanhang Zhang Shuang Yang Shiguang Shan Xilin Chen Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

We propose a novel strategy, ES 3 , for self-supervised learning of robust audio-visual speech representations from unlabeled talking face videos. While many recent approaches for this task primarily rely on guiding the learning process using the audio modality alone to capture information shared between audio and video, we reframe the problem as the acquisition of shared, unique (modality-specific) and synergistic speech information to address the inherent asymmetry between the modalities. Based on this formulation, we propose a novel “evolving” strategy that progressively builds joint audio-visual speech representations that are strong for both uni-modal (audio & visual) and bi-modal (audio-visual) speech. First, we leverage the more easily learnable audio modality to initialize audio and visual representations by capturing audio-unique and shared speech information. Next, we incorporate video-unique speech information and bootstrap the audio-visual repre-sentations on top of the previously acquired shared knowledge. Finally, we maximize the total audio-visual speech information, including synergistic information to obtain robust and comprehensive representations. We implement ES 3 as a simple Siamese framework and experiments on both English benchmarks and a newly contributed large-scale Mandarin dataset show its effectiveness. In particular, on LRS2-BBC, our smallest model is on par with SoTA models with only 1/2 parameters and 1/8 unlabeled data (223h).

关键词： Visualization Computer vision Self-supervised learning Manuals Benchmark testing Data models Pattern recognition

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Efficient DOA Estimation Based on Cauchy Loss Variable Step Size Algorithm

Efficient DOA Estimation Based on Cauchy Loss Variable Step ...

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IEEE International Conference on Electronic information and Communication Technology (ICEICT)

作者： Xingchao Xu Yingsong Li College of Information and Communications Engineering Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

The Cauchy loss function is robust to large outliers and has successful applications in signal processing. In this paper, a DOA estimation algorithm based on adaptive zero technology is proposed, which updates the weight of the filter by applying the Cauchy loss function, and further improves the algorithm performance by using the variable step size method. The algorithm step size is adjusted by accumulating errors and establishing a nonlinear function with instantaneous errors. The DOA estimation ability, estimation error and accuracy of the improved Cauchy algorithm in the impulse noise environment are analyzed. The algorithm is verified by simulation experiments.

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Design of Control Circuit for Active Metasurface Based on Varactor Diode

Design of Control Circuit for Active Metasurface Based on Va...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Yue Zhang Yuefei Liu Guohui Yang Kuang Zhang Yingsong Li School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

A control circuit for active metasurface based on varactor diode is designed in this paper. By varying the reverse bias voltage on the varactor diode, the designed circuit can regulate the additional phase of the active meta-atoms. The circuit adopts a form of one master and multiple slaves, which can simultaneously control the bias voltage of 960 meta-atoms. Each slave can control up to 64 channels. The control accuracy is 0.04V. The power consumption of a single slave is 160mW. Though experiment verification, the circuit has a good effect in controlling the beam deflection of the metasurface and generating OAM beams.

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TOP: Towards Better Toxicity Prediction by Deep Molecular Representation Learning

TOP: Towards Better Toxicity Prediction by Deep Molecular Re...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yuzhong Peng Ziqiao Zhang Qizhi Jiang Jihong Guan Shuigeng Zhou Key Lab of Scientific Computing Intelligent Information Processing in Universities of Guangxi Nanning Normal University Nanning China Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Tongji University Shanghai China

At the early stages of the drug discovery, molecule toxicity prediction is crucial to excluding drug candidates that are likely to fail in clinical trials. In this paper, we presented a novel molecular representation method and developed a corresponding deep learning-based framework called TOP (the abbreviation of TOxicity Prediction). TOP integrated a serial special data processing methods, a bidirectional gated recurrent unit-based RNN (BiGRU) and a fully connected neural network for end-to-end molecular representation learning and chemical toxicity prediction. TOP can automatically learn a mixed molecular representation from not only SMILES contextual information that describes the molecule structure, but also physiochemical properties. Therefore, TOP can overcome the drawbacks of existing methods that use either of them, thus greatly promotes toxicity prediction. We conducted extensive experiments over 14 classic toxicity prediction tasks on three different benchmark datasets, including balanced and imbalanced ones. The results show that, with the help of the novel molecular representation method, TOP significantly outperforms not only three baseline machine learning methods, but also five state-of-the-art methods.

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Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Driving

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年第5期9卷 1-19页

作者： Li, Yueyuan Yuan, Wei Zhang, Songan Yan, Weihao Shen, Qiyuan Wang, Chunxiang Yang, Ming Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Innovation Center of Intelligent Connected Vehicle Global Institute of Future Technology Shanghai Jiao Tong University Shanghai China Global Institute of Future Technology Shanghai Jiao Tong University Shanghai China

Simulators play a crucial role in autonomous driving, offering significant time, cost, and labor savings. Over the past few years, the number of simulators for autonomous driving has grown substantially. However, there is a growing concern about the validity of algorithms developed and evaluated in simulators, indicating a need for a thorough analysis of the development status of the simulators. To address existing gaps in research, this paper undertakes a comprehensive review of the history of simulators, proposes a utility-based taxonomy, and investigates the critical issues within open-source simulators. Analysis of the past thirty years' development trajectory reveals a trend characterized by an increase in open-source simulators and an expansion of their functionality scope. The categorization of simulators based on feature functionalities delineates five primary classes: traffic flow, sensory data, driving policy, vehicle dynamics, and comprehensive simulators. Furthermore, the paper identifies critical unresolved issues in open-source simulators, including concerns regarding the fidelity of sensory data, representation of traffic scenarios, and accuracy in vehicle dynamics simulation, all of which have the potential to undermine experimental confidence. Additionally, challenges in data format inconsistency, labor-intensive map construction processes, sluggish step updating, and insufficient support for Hardware-In-the-Loop testing are discussed as hindrances to experimental efficiency. In light of these findings, the survey furnishes task-oriented recommendations to aid in the selection of simulators, taking into account factors such as accessibility, maintenance status, and quality, while highlighting the inherent limitations of existing open-source simulators in validating algorithms and facilitating real-world experimentation. IEEE

关键词： Autonomous vehicles

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