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        2019-08-01來源: 瀏覽次數:

        “綜合電子信息系統”科技部國際科技合作基地首屆國際學術研討會(International Symposium on Multi-modal Sensing and Information Processing, ISMSIP 2019)定于8月4 - 5日在西安志誠麗柏酒店20樓會議室舉行。大會邀請到來自美國和英國著名高校的IEEE Fellow等多位相關領域知名專家學者做特邀報告。







        International Symposium on Multi-modal Sensing and Information Processing 2019

        ISMSIP2019 Schedule
        Venue: Ziction Liberal Hotel(西安志誠麗柏酒店), 20th floor Conference Room
        Aug 4  Morning
        08:30-09:00 Opening Ceremony
        09:00-09:40 Introduction to Decomposition Based Multiobjective Evolutionary Computation Qingfu ZHANG
        09:40-10:20 3D Modeling Technology for Cultural Heritage Protection and Smart City Xianfeng HUANG
        Tea break(20min)
        10:40-11:20 Graph signal processing: fundamentals and distributed algorithms Junzheng JIANG
        11:20-12:00 Deep Learning With Applications To Radar Target Detection and Recognition Lan DU
        Lunch time
        Aug 4  Afternoon
        14:30-15:10 The Tail-null-space-property and the Stability of the Tail-minimization Approach in Compressed Sensing with or without Frames Shidong LI
        15:10-15:50 Sparse Bayesian Algorithms for Signal Recovery Ningning HAN
        15:50-16:30 Infinite-Dimensional Compressed Sensing and Spectral Analysis of Signals Zai YANG
        Tea break(20min)
        16:50-17:30 Transmit Signal Design for Large-Scale MIMO System With One-Bit DACs Bin LIAO
        17:30-18:10 From Random Vectors to Random Matrices: Asymptotics of Empirical Eigenvalues for Large Separable Covariance Matrices TieBin MI
        Aug 5  Morning
        08:30-09:10 Defect-Detecting Technology for over 100-meter-Shaft under the Disaster Luliang TANG
        09:10-09:50 Area Coverage and Target Tracking for Mobile sensor networks Gang WANG
        Tea break(20min)
        10:10-10:50 A Fast Implementation of Interactive Multi-Model Generalized Labeled Multi-Bernoulli Filter for Interval Measurements Sunyong WU
        10:50-11:30 Sparse Frame DOA Estimations via Rand-one Correlation Model for Low SNR and Limited Snapshots Cao ZENG

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