There is a big growth in the application of machine learning to electronics test. You can see below that there are many topics related to machine learning. Some really interesting applications.
Will the singularity take over test?
Sunday Tutorial:
Tutorial 3: Learning Techniques for Reliability Monitors, Mitigation and Adaptation
Tutorial 6: Machine Learning for Test & Test for Machine Learning
Monday Tutorial:
Tutorial 9: From Data to Actions: Applications of Data Analytics in Semiconductor Manufacturing & Test
Technical Sessions:
Special Session on Machine Learning:
Paper S4.1: The Emerging Applications of Machine Learning in Testing
Paper S4.2: Enhanced Lithographic Hotspot Detection Through Design of Experiments
Paper S4.3: Opportunities in Machine Learning and Test
Also see:
Paper 2.3: Systematic Defect Detection Methodology for Volume Diagnosis: A Data Mining Perspective
Paper 9.1: Kernel-based Clustering for Quality Improvement and Excursion Detection
Paper 12.1: Automated Die Inking: A Pattern Recognition-based Approach
Paper 12.3: ITC-India Best Paper: Cognitive Approach to Support Dynamic Aging Compensation
Paper 13.2: Changepoint-based Anomaly Detection in a Core Router System
Paper 13.3: Symbol-based Health-Status Analysis in a Core Router System
Paper 14.3: Some Considerations on Choosing an Outlier Method for Automotive Product Lines
Panel P3: Yield Learning at the Crossroads – Test Chips to the Rescue?
DATA Workshop – Machine Learning Day (Friday, Nov 2nd):
Keynote on Machine Learning, presented by Siemens
Talk 1: Machine Learning – Analog Test, ChoonWee Koay
Talk 2: Machine Learning – Synergy, Sam Joneidi
Talk 3: Machine Learning – Diagnosis, presented by CMU group
Talk 4: Machine Learning – Wafer Application, presented by UT-Dallas group
Talk 5: Machine Learning – System Test, presented by Duke group
Talk 6: Machine Learning – Production Yield, presented by UCSB group
Talk 7: Machine Learning – Security, Al Crouch
2018 ITC in Phoenix
/in Headlines /by Anne GattikerJoin us in 2018 ITC in Phoenix Arizona at the Phoenix Convention Center. Hotel reservations can be made from the “register” link in the main menu.
ITC will be co-located with ISTFA in 2018.
We will take advantage of sharing in some activities between our two conferences. Co-location provides some great benefits to the attendees:
Network with almost two thousand attendees
Shared keynote and select parts of the technical program
See over 150 solutions providers on the shared exhibit floor
Registration option for access to both conferences
See more on the Phoenix Convention Center and interesting nightlife
Gerald W. Gordon Award
/0 Comments/in Headlines /by Ron PressITC Is Now Accepting Nominations for the 2018 Gerald W. Gordon Award for Student Volunteerism
The International Test Conference (ITC) , the Test Technology Technical Council and the IEEE Philadelphia Section sponsor the Gerald W. Gordon Award. The award to the recipient consists of complimentary tutorial registration for one morning and one afternoon tutorial for each of the 2 days they are offered, complimentary full conference registration for ITC, complimentary registration for one of the at conference workshops, up to $750 for travel expenses to the conference and free lodging for the nights of attendance.
Eligibility Requirements
The Gerald W. Gordon Award recipient must be a student in good standing at an accredited university or college. Award recipients must have done volunteer work for one or more IEEE conferences, symposia, workshops and/or organizations dedicated to the development of electronics design and testing fields.
Consideration shall be given to the amount of volunteer service given; the breadth of volunteer service given; the impact of the volunteer service give; and worthiness of the candidate.
Nomination Process
The form for nominating a candidate can be obtained by clicking on the following link, “2018 Gerald W. Gordon Award Nomination form”. The nominator must complete and submit an application form to summarize why the applicant is qualified for the award and list the relevant service work. In addition, the nominator must identify 2, but not more than 5 endorsers. The nominator must inform the endorsers that they need to email an endorsement of the candidate as described on the nomination form. The nomination form and endorsement emails should be sent to Kenneth Mandl at mandlken@aol.com and Yervant Zorian at Yervant.Zorian@synopsys.com. No later than September 24, 2018. All candidates will be notified of the selection decision by October 1, 2018.
Machine Learning during testweek
/0 Comments/in Headlines /by Ron PressThere is a big growth in the application of machine learning to electronics test. You can see below that there are many topics related to machine learning. Some really interesting applications.
Will the singularity take over test?
Sunday Tutorial:
Tutorial 3: Learning Techniques for Reliability Monitors, Mitigation and Adaptation
Tutorial 6: Machine Learning for Test & Test for Machine Learning
Monday Tutorial:
Tutorial 9: From Data to Actions: Applications of Data Analytics in Semiconductor Manufacturing & Test
Technical Sessions:
Special Session on Machine Learning:
Paper S4.1: The Emerging Applications of Machine Learning in Testing
Paper S4.2: Enhanced Lithographic Hotspot Detection Through Design of Experiments
Paper S4.3: Opportunities in Machine Learning and Test
Also see:
Paper 2.3: Systematic Defect Detection Methodology for Volume Diagnosis: A Data Mining Perspective
Paper 9.1: Kernel-based Clustering for Quality Improvement and Excursion Detection
Paper 12.1: Automated Die Inking: A Pattern Recognition-based Approach
Paper 12.3: ITC-India Best Paper: Cognitive Approach to Support Dynamic Aging Compensation
Paper 13.2: Changepoint-based Anomaly Detection in a Core Router System
Paper 13.3: Symbol-based Health-Status Analysis in a Core Router System
Paper 14.3: Some Considerations on Choosing an Outlier Method for Automotive Product Lines
Panel P3: Yield Learning at the Crossroads – Test Chips to the Rescue?
DATA Workshop – Machine Learning Day (Friday, Nov 2nd):
Keynote on Machine Learning, presented by Siemens
Talk 1: Machine Learning – Analog Test, ChoonWee Koay
Talk 2: Machine Learning – Synergy, Sam Joneidi
Talk 3: Machine Learning – Diagnosis, presented by CMU group
Talk 4: Machine Learning – Wafer Application, presented by UT-Dallas group
Talk 5: Machine Learning – System Test, presented by Duke group
Talk 6: Machine Learning – Production Yield, presented by UCSB group
Talk 7: Machine Learning – Security, Al Crouch