Danilo Avola

发布者:沈梦妍发布时间:2024-05-10浏览次数:10

《数字内容处理》课程负责人介绍


(一)个人简介

Danilo Avola 老师于 2014 年毕业于拉奎拉大学,获得分子和超微结构成像学博士学位,并 2018 年入职罗马第一大学,目前为社会研究与传播学院教师。Danilo Avola 老师主要研究方向为人机交互,计算机视觉,信号处理,机器学习,深度学习,图像和视频处理,担任的社会兼职包括意大利罗马国家研究委员会(National Research Council)多模式与多媒体(MM实验室研究工程师。

(二)主讲课程

1.  通信信息技术和数字通信技术

2.  数字内容处理

3.  管理与创新经济学及传播

(三)主要成就

Danilo Avola 老师从事科研工作以来,已出版学术著作多部,并在《Journal of biomedical informatics》等重要期刊发表学术论文多篇。主要学术成果如下:

1. Avola D, Bernardi M, Cinque L, et al. Exploiting recurrent neural networks and leap motion controller for the recognition of sign language and semaphoric hand gestures[J]. IEEE Transactions on Multimedia, 2018, 21(1): 234-245.

2. Avola D, Spezialetti M, Placidi G. Design of an efficient framework for fast prototyping of customized human–computer  interfaces  and  virtual  environments  for  rehabilitation[J].  Computer Methods and Programs in Biomedicine, 2013, 110(3): 490-502.

3. Avola D, Spezialetti M, Placidi G. Design of an efficient framework for fast prototyping of customized human–computer  interfaces  and  virtual  environments  for  rehabilitation[J].  Computer Methods and Programs in Biomedicine, 2013, 110(3): 490-502.

4. Avola D, Bernardi M, Foresti G L. Fusing depth and colour information for human action recognition[J]. Multimedia Tools and Applications, 2019, 78(5): 5919-5939.

5.  Placidi  G,  Avola  D,  Petracca  A,  et  al.  Basis  for  the  implementation  of  an  EEG-based single-trial binary brain computer interface through the disgust produced by remembering unpleasant odors[J]. Neurocomputing, 2015, 160: 308-318.

6. Avola D, Cinque L, Foresti G L, et al. A keypoint-based method for background modeling and foreground detection using a PTZ camera[J]. Pattern Recognition Letters, 2017, 96: 96- 105.

7. Avola D, Cinque L, Foresti G L, et al. A UAV video dataset for mosaicking and change detection  from  low-altitude  flights[J].  IEEE  Transactions   on   Systems,  Man,   and  Cybernetics: Systems, 2018, 50(6): 2139-2149.

8. Avola D, Cascio M, Cinque L, et al. 2-D skeleton-based action recognition via two-branch stacked LSTM-RNNs[J]. IEEE Transactions on Multimedia, 2019, 22(10): 2481-2496.

9. Avola D, Cinque L, Foresti G L, et al. VRheab: A fully immersive motor rehabilitation system based   on   recurrent   neural   network[J].   Multimedia   Tools   and   Applications,   2018,   77(19): 24955-24982.

10. Placidi G, Avola D, Iacoviello D, et al. Overall design and implementation of the virtual glove[J]. Computers in biology and medicine, 2013, 43(11): 1927- 1940.

11. Avola D, Bernardi M, Cinque L, et al. Adaptive bootstrapping management by keypoint clustering for background initialization[J]. Pattern Recognition Letters, 2017, 100: 110- 116.

12. Moro S B, Carrieri M, Avola D, et al. A novel semi-immersive virtual reality visuo-motor task  activates  ventrolateral  prefrontal   cortex:   a  functional  near-infrared   spectroscopy  study[J]. Journal of neural engineering, 2016, 13(3): 036002.

13. Avola D, Cinque L, De Marsico M, et al. LieToMe: Preliminary study on hand gestures for deception detection via Fisher-LSTM[J]. Pattern Recognition Letters, 2020, 138: 455-461.

14. Placidi G, Avola D, Ferrari M, et al. A low-cost real time virtual system for postural stability assessment at home[J]. Computer methods and programs in biomedicine, 2014, 117(2): 322-333.

15. Avola D, Bernardi M, Cinque L, et al. Fusing Self-Organized Neural Network and Keypoint Clustering for Localized Real-Time Background Subtraction[J]. Int. J. Neural Syst., 2020, 30(4): 2050016:1-2050016:17.


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