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郎波

(北京師範大學珠海分校信息技術學院副教授)

鎖定
郎波,男,中國國籍,北京師範大學珠海分校信息技術學院副教授,復旦大學博士畢業,現任信息技術學院數字媒體技術繫系主任。
中文名
彭波
國    籍
中國
性    別

郎波承擔課程

《程序設計基礎》、《數據結構》、《面向對象程序設計》。
研究領域與科研方向
圖像特徵提取、智能媒體技術

郎波科研成果

1、科研項目
1國家自然科學基金項目、61375122、基於數值方法的大腦神經迴路與功能集團結構研究、2014/01-2017/12、
2國家自然科學基金項目、81373556、基於舌象圖像矢量模型的中醫證候療效評價支持方法研究、2014/01-2017/12
3國家重點基礎研究發展973計劃項目、2010CB327900、數字媒體理解的理論與方法研究、2009/09-2014/09、
4國家自然科學基金項目、30990263、額葉和海馬環路的理論建模和腦機接口、2010/01-2013/01、 [1] 
發表論文
[1] Lang Bo, Zuo Qingsong, A Bio-inspired Image Representation Model using non-Classical Receptive Field, Proceedings-International Conference on Engineering Applications of Neural Network, 2011,pp 576-587
[2], Zuo Qingsong, Lang Bo, A Bio-inspired model for image representation and image analysis,Proceedings-International Conference on Tools With Artificial Intelligence, 2011,pp 409-413
[3] Zuo Qingsong,Lang Bo, Multi-scale Image Analysis Based on non-Classical Receptive Field Mechanism, Lecture Notes in Computer Science, 2011, Volume 7064,pp 601-610
[4] ,Lang Bo, Zuo Qingsong, An Image Representation Method Based on Retina Mechanism for the Promotion of SIFT and Segmentation, Lecture Notes in Computer Science, 2012,Volume 7667,pp 378-385
[5] Lang Bo, Wei Hui*, , Zuo Qingsong, Contour Detection Model with Multi-scale Integration based on Non-classical Receptive Field, Neurocomputing, 2013,Volume 103,pp 247-262
[6]Hui Wei*, Qingsong Zuo, Bo Lang: A General Image Representation Scheme and Its Improvement for Image Analysis. Lecture Notes in Computer Science,2013, Volume 8131,pp 359-366
[7],Lang Bo,Zuo Qingsong, An Image Representation Infrastructure based on Non-classical Receptive Fields, Soft Computing, 2014 ,Volume 18, Issue 1, pp 109-123
[8]樊一娜、郎波*,危輝,基於貝葉斯原理的多維Spike train分類預測模型,《電子與信息學報》,2013,Vol.35(7):1619-1623
[9]郎波、黃靜、危輝,利用多層視覺網絡模型進行圖像局部特徵表徵的方法,《計算機輔助設計與圖形學學報》,2014,已錄用
[10]Lang Bo, Huang Jing, A general image representation scheme and its improvement for image analysis.Proceedings-International Conference on System and Information,2014,已錄用
11Lang Bo, Fan Yi-na, Huang Jing, A bio-inspired model of image representation based on non-classical receptive fields Proceedings-International Conference on System and Informati,2014,已錄用 [2] 
參考資料