《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，并于 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（M＆M）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.
