'Training procedure' diaporamas de présentation

A lifetime of training for just ten seconds. Jesse Owens

1.03k views • 89 slides

Confidence Measures for Automatic Speech Recognition

Confidence Measures for Automatic Speech Recognition. National Taiwan Normal University Spoken Language Processing Lab. Advisor : Hsin-Min Wang Berlin Chen. Presented by Tzan-Hwei Chen. Outline. Introduction The category of estimation methods of confidence measure (CM)

730 views • 62 slides

Outline

Outline. Concept of Learning Basis of Artificial Neural Network Neural Network with Supervised Learning (Single Layer Net) Hebb Perceptron Modelling Simple Problem. CONCEPT OF LEARNING. Nooraini Yusoff Computer Science Department Faculty of Information Technology

788 views • 52 slides

Outline

Outline. Concept of Learning Basis of Artificial Neural Network Neural Network with Supervised Learning (Single Layer Net) Hebb Perceptron Modelling Simple Problem. CONCEPT OF LEARNING. Nooraini Yusoff Computer Science Department Faculty of Information Technology

523 views • 52 slides

Introduction to Neural Networks

Introduction to Neural Networks. John Paxton Montana State University Summer 2003. Chapter 2: Simple Neural Networks for Pattern Classification. x 0. 1. w 0. w 0 is the bias f(y in ) = 1 if y in >= 0 f(y in ) = 0 otherwise ARCHITECTURE. y. w 1. x 1. w n. x n. Representations.

513 views • 31 slides

Training for Clients

Training for Clients. Introductions. Nearly All Websites Fail. Why Do Websites Fail?. Unrealistic expectations Lack of knowledge Failure to see websites as a process. 4 Training Decisions. Content Methods Media Results. Content.

382 views • 31 slides

Introduction to Neural Networks

Introduction to Neural Networks. John Paxton Montana State University Summer 2003. Chapter 2: Simple Neural Networks for Pattern Classification. x 0. 1. w 0. w 0 is the bias f(y in ) = 1 if y in >= 0 f(y in ) = 0 otherwise ARCHITECTURE. y. w 1. x 1. w n. x n. Representations.

342 views • 31 slides

Protein-Protein Interactions

Protein-Protein Interactions. Protein Quaternary Structure. No covalent bonding. Homo- oligimer vs Hetero- oligimer. Protein Complex. Subunits = each protein Protein complex performs a biological function. To the left is the proteasome. Degrades unneeded and damaged proteins

585 views • 28 slides

Computer Vision CS 776 Spring 2014

Computer Vision CS 776 Spring 2014. Recognition Machine Learning Prof. Alex Berg. Recognition: A machine learning approach. Slides adapted from Svetlana Lazebnik , Fei -Fei Li, Alex Berg, Rob Fergus, Antonio Torralba , Kristen Grauman , and Derek Hoiem.

388 views • 26 slides

Psychology of Learning EXP4404

Psychology of Learning EXP4404. Chapter 10: Generalization, Discrimination, and Stimulus Control Dr. Steve. Topics Covered. Generalization Measurement Semantic Generalization Discrimination Discrimination Training S D vs. S ? Procedures Stimulus Control

401 views • 23 slides

Model-based Automatic Detection of the Anterior and Posterior Commissures on MRI Scans

Model-based Automatic Detection of the Anterior and Posterior Commissures on MRI Scans. Babak A. Ardekani and Alvin H. Bachman Presented by Dazhou Guo. Introduction.

332 views • 18 slides

Goals : Down sample 20 khz TIDigits data to 16 khz .

Goals : Down sample 20 khz TIDigits data to 16 khz . 2. Use Down sample data run regression test and Compare results posted in Sphinx-4 website 3. Based on the results, make decisions (issue with microprocessor, floating point etc .) By Jaykrishna shukla , Mubin Ahmed and Cara Santin.

360 views • 16 slides

Best Online Corporate Training Programs in Bangalore

Seleniumlabs is one of the best Selenium training institutes in Bangalore, popular for its professional training. This is one stop solution for providing training services in Information Technology, Software Education & End-to-End solutions. Read More :www.seleniumlabs.in

162 views • 9 slides

Preliminary Results (Synthetic Data)

Fast and Accurate Prediction via Evidence-Specific MRF Structure Veselin Stoyanov and Jason Eisner Johns Hopkins University. G 2. G 1. G 1. G 4. G 6. B. G 3. A. G 1. G 5. C. G 7. F. D. E. Gates

109 views • 1 slides