研究生培養

宋巍（教授）

發布者：張程冬發布時間：2024-03-26浏覽次數：4909

  

宋巍 Wei SONG (Professor, Ph.D)


姓名 Name：

宋巍 Wei Song

導師類别Supervision：

碩導、博導 Master and Doctoral Supervisor

所在專業Discipline：

軟件工程

Software Engineering

研究方向 Research Interests：

計算機視覺 Computer vision

海洋大數據分析 Marine big data analysis

學院/單位 Department：

伟德BETVLCTOR College of Information Technology

郵箱E-Mail：

wsong@shou.edu.cn

通訊地址 Address：

上海市浦東新區滬城環路999号, 201306

No.999 Hu Cheng Huan Road, Pudong New Area, Shanghai 201306

簡介 Introduction：

宋巍教授，省部級人才計劃獲得者，主要從事計算機視覺、海洋大數據分析等方向研究，在水下視覺增強、海冰分類、海浪信息檢測預測等領域開展了系統性研究。近年來主持國家自然科學基金項目2項和上海市科委項目2項。出版《Marine Big Data》英文專著1部，在國内外重要期刊和國際會議上發表學術論文80餘篇，獲得授權發明專利10項，獲上海市教學成果二等獎、上海海洋科學技術一等獎、上海市總工會“科創中心建設”競賽科研項目二等獎，國家産學研合作創新成果獎一等獎等。

Dr. Song, awarded by the Shanghai Talent Program, is mainly engaged in computer vision, ocean big data analysis, and the related applications. She has carried out systematic research in the fields of underwater vision enhancement, sea ice classification, and ocean wave information detection and prediction. In recent years, she has presided over two projects of the National Natural Science Foundation and two projects of the Shanghai Science and Technology Commission. She has published an English monograph on "Marine Big Data", more than 80 academic papers in important journals and international conferences, obtained 10 patents, and won multiple awards, including the Second Prize of Shanghai Teaching Achievement, the First Prize of Shanghai Marine Science and Technology Award, the First Prize of the National Industry-University-Research Cooperation Innovation Achievement Award, etc.

教育經曆 Education：

09/2008 – 10/2012 博士(Ph.D)

昆士蘭科技大學(Queensland University of Technology, Brisbane, Australia)

09/2005 – 07/2008 工學碩士(Ms.E)

太原理工大學 （Taiyuan University of Technology, Taiyuan, Shanxi Province, China)

工作經曆 Working Experience

2016.1- 至今 教授Professor

伟德BETVLCTOR (Shanghai Ocean University)

2012 - 2015.11研究員 Research Fellow

澳大利亞昆士蘭科技大學 (Queensland University of Technology)

獲獎情況 Awards

  1. 2022年上海市教學成果獎 二等獎 （the second prize of Shanghai Teaching Achievement）

  2. 2021年上海海洋科學技術獎 一等獎 (the first prize of Shanghai Marine Science and Technology Award)

  3. 2020年上海市總工會“奮進新時代創造新奇迹競賽”科創競賽項目 二等獎 (the second prize of Science Innovation Competition Project by Shanghai Federation of Trade Unions)

  4. 2018年，上海市浦東新區科學技術獎 二等獎 (the second prize of Science and Technology Award of Shanghai Pudong New Area)

  5. 2017年獲得中國産學研合作創新成果 一等獎 (the first prize of National Industry-University-Research Cooperation Innovation Achievement Award)

  6. 指導全國研究生數學建設競賽獲得二等獎2次、三等獎5次

承擔的科研項目Scientific research projects undertaken：

  1. 國家“十四五”重點研發計劃（National Key R&D Project), No.2021YFC3101601, 2021-2025, 參與（CI）

  2. 國家自然科學基金面上項目 (National Natural Science Foundation of China, NSFC), No.61972240, 2019.1.1-2023.12.31, 主持 (PI)

  3. 國家自然科學基金青年項目 (National Natural Science Foundation of China for Youth), No.41906179, 2018.1.1-2020.12.31，主持 (PI)

  4. 上海市科委部分地方高校能力建設項目 (Program for capacity building of local colleges and universities funded by Shanghai Science and Technology Commission)，No.20050501900, 2020.10.1-2023.9.30，主持 (PI)

  5. 上海市科委部分地方高校能力建設項目(Program for capacity building of local colleges and universities funded by Shanghai Science and Technology Commission)，No.17050501900, 2017.7.1 - 2020.6.30，主持 (PI)

代表性論著 Representative publications：

Book & Book Chapters:

  1. HUANG D, SONG W, ZOU G, Marine Big Data [M]. World Scientific Publishing. 2019, ISDN:9789811202483

  2.  SONG W.,Tjondronegoro, D., and Docherty, M..  User-centered study on quality of mobile video services [M]. In Tjondronegoro, D.  (Eds.), Tools for Mobile Multimedia Programming and Development. IGI Global, 2013.

  3. SONG W., Tjondronegoro, D., and Docherty, M. Understanding user experience of mobile video: Framework, measurement,  and optimization[M]. In Tjondronegoro, D. (Eds.), Mobile Multimedia – User  &Technology Perspectives, InTech Open Access, 2012.

Journals:

  1. XU S, ZHANG M, SONG W*, et al. A systematic review and analysis of deep learning-based underwater object detection[J/OL]. Neurocomputing, 2023, 527: 204-232. DOI:10.1016/j.neucom.2023.01.056.

  2. WANG J, LI X, ZHANG Z, SONG W*, GUO WQ. Ranked Similarity Weighting and Top-nk Sampling in Deep Metric Learning[J/OL]. IEEE Transactions on Multimedia, 2022: 1-10. DOI:10.1109/TMM.2022.3225738.

  3. SONG W, LI H, HE Q, et al. E-MPSPNet: Ice–Water SAR Scene Segmentation Based on Multi-Scale Semantic Features and Edge Supervision[J/OL]. Remote Sensing, 2022, 14(22): 5753. DOI:10.3390/rs14225753.

  4. LIU X, SONG W*, HE Q, et al. Speeding Up Subjective Video Quality Assessment via Hybrid Active Learning[J/OL]. IEEE Transactions on Broadcasting, 2022: 1-14. DOI:10.1109/TBC.2022.3210385.

  5. WANG Y, SONG W, TAO W, et al. A systematic review on affective computing: emotion models, databases, and recent advances[J/OL]. Information Fusion, 2022, 83-84: 19-52. DOI:10.1016/j.inffus.2022.03.009.

  6. SONG W, GAO W, HE Q, et al. SI-STSAR-7: A Large SAR Images Dataset with Spatial and Temporal Information for Classification of Winter Sea Ice in Hudson Bay[J/OL]. Remote Sensing, 2021, 14(1): 168. DOI:10.3390/rs14010168.

  7. SONG W, LI M, GAO W, et al. Automatic Sea-Ice Classification of SAR Images Based on Spatial and Temporal Features Learning[J/OL]. IEEE Transactions on Geoscience and Remote Sensing, 2021, 59(12): 9887-9901. DOI:10.1109/TGRS.2020.3049031.

  8. ZHANG M, XU S, SONG W*, et al. Lightweight Underwater Object Detection Based on YOLO v4 and Multi-Scale Attentional Feature Fusion[J/OL]. Remote Sensing, 2021, 13(22): 4706. DOI:10.3390/rs13224706.

  9. DU Y, SONG W*, HE Q, et al. Deep learning with multi-scale feature fusion in remote sensing for automatic oceanic eddy detection[J/OL]. Information Fusion, 2019, 49: 89-99. DOI:10.1016/j.inffus.2018.09.006.

  10. SONG W, WANG Y, HUANG D, et al. Enhancement of Underwater Images With Statistical Model of Background Light and Optimization of Transmission Map[J/OL]. IEEE Transactions on Broadcasting, 2020, 66(1): 153-169. DOI:10.1109/TBC.2019.2960942.

  11. WANG Y, SONG W*, FORTINO G, et al. An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging[J/OL]. IEEE Access, 2019: 1-1. DOI:10.1109/ACCESS.2019.2932130.

Conferences:

  1. WANG Y, SUN Y, SONG W, et al. DPCNet: Dual Path Multi-Excitation Collaborative Network for Facial Expression Representation Learning in Videos[C/OL]//Proceedings of the 30th ACM International Conference on Multimedia. Lisboa Portugal: ACM, 2022: 101-110.

  2. WANG J, LI X, SONG W, ZHANG Z, GUO W. Multi-Hierarchy Proxy Structure for Deep Metric Learning[C/OL]//ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Singapore, Singapore: IEEE, 2022: 1645-1649.

  3. SONG W, LI Q, HE Q, ZHOU X, CHEN Y. Determining Wave Height from Nearshore Videos Based on Multi-level Spatiotemporal Feature Fusion[C]//2021 International Joint Conference on Neural Networks (IJCNN). 2021Shenzhen, China: : 1–8.

  4. WANG J, ZHANG Z, HUANG D, Song W, WEI Q, LI X. IEEE, 2021. A Ranked Similarity Loss Function with pair Weighting for Deep Metric Learning[C]//ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021Toronto, Canada: 1760–1764.

  5. SONG W, DAI S, HUANG D, SONG J, ANTONIO L. Median-Pooling Grad-CAM: An Efficient Inference Level Visual Explanation for CNN Networks in Remote Sensing Image Classification[G]//LOKOČ J, SKOPAL T, SCHOEFFMANN K, 等. MultiMedia Modeling. Springer International Publishing, 2021 , 12573: 134–146.

  6. SONG W, WANG Y, HUANG D, TJONDRONEGORO D. A Rapid Scene Depth Estimation Model Based on Underwater Light Attenuation Prior for Underwater Image Restoration[M/OL]//HONG R, CHENG W H, YAMASAKI T, et al. Advances in Multimedia Information Processing – PCM 2018: 11164. Cham: Springer International Publishing, 2018: 678-688

  

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