'Temporal features' diaporamas de présentation

Huadong Xia, Christopher Barrett, Jiangzhuo Chen, Madhav Marathe

IEEE BDSE2013. Computational Methods for Testing Adequacy and Quality of Massive Synthetic Proximity Social Networks. Huadong Xia, Christopher Barrett, Jiangzhuo Chen, Madhav Marathe. Network Dynamics and Simulation Science Laboratory Virginia Tech NDSSL TR-13-153. Acknowledgement.

544 views • 43 slides

Envelope and TFS arise from a method of decomposing waveforms

631 views • 37 slides

Detecting Prosody Improvement in Oral Rereading

Detecting Prosody Improvement in Oral Rereading. Minh Duong and Jack Mostow Project LISTEN www.cs.cmu.edu/~listen Carnegie Mellon University.

254 views • 25 slides

Discovering Regions of Different Functions in a City Using Human Mobility and POIs

Discovering Regions of Different Functions in a City Using Human Mobility and POIs. Presented By Ningzhou Zeng April 7, 2014. I ntroduction.

405 views • 24 slides

Cyclic input of characters through a single digital button without visual feedback

Cyclic input of characters through a single digital button without visual feedback. Yang Xiaoqing xiaoqing.yang@uta.fi. New Interaction Techniques Dept. of Computer and Information Sciences University of Tampere 25.02.2003. Introduction to the problem.

252 views • 14 slides

Progression Modelling for Online and Early Gesture Detection

Progression Modelling for Online and Early Gesture Detection. Sai Kumar Dwivedi Mercedes-Benz R&D India. Rishabh Dabral IIT Bombay. Arjun Jain IIT Bombay, Axogyan AI. Vikram Gupta Mercedes-Benz R&D India. Gestures are Everywhere. Goals.

114 views • 11 slides

Vishal K. Singh Henning Schulzrinne Hannes Tschofenig IETF 70, Vancouver

Dynamic Feature Extensions to the Presence Information Data Format Location Object (PIDF-LO) draft-singh-geopriv-pidf-lo-dynamic-02.txt. Vishal K. Singh Henning Schulzrinne Hannes Tschofenig IETF 70, Vancouver. Requirements and Use Cases.

176 views • 10 slides

Data Driven Attributes for Action Recognition

Data Driven Attributes for Action Recognition. Week 9 Presented by Christina Peterson. Recognition Accuracies on UCF Sports data set. Confusion Matrix: Standard Multi-Class SVM. Di. Go. Ki. Li. Ho. Ru. Sk. Sb. Ss. Wa. Diving. Golf. Kick. Lift. Horse-Ride. Run. Skateboard.

167 views • 7 slides