Convolutional Neural Networks and Deep Machine learning
IEEE Seminar: Convolutional Neural Networks and Deep Machine learning
This tutorial starts with a brief overview of Machine learning and Neural Networks. It proceeds to offer an in-depth treatment of Convolutional neural networks(CNN) and deep machine learning. It also covers various architecture optimization techniques including data optimization, dropouts,layer patterns and sizing. It provides CNN visualization and a comprehensive case study of recent CNN architectures including AlexNet, ZFNet and GoogleNet.
Date and Time
Location
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- IIIT Hyderabad Campus
- Gachibowli
- HYDERABAD, Andhra Pradesh
- India 500032
- Room Number: H203
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- Contact Event Host
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Bala Prasad Peddigari Chairman IEEE Computer Society- Hyderabad Section Phone: 9295081188
Email: balasparks@gmail.com / bala.peddigari@ieee.org
- Co-sponsored by Bala Prasad Peddigari
- Starts 20 July 2017 06:30 AM UTC
- Ends 26 July 2017 09:30 AM UTC
- 0 in-person spaces left!
- No Admission Charge
Speakers
Kiran Gunnam of Velodyne Lidar Inc
Convolutional Neural Networks and Deep Machine learning
This tutorial starts with a brief overview of Machine learning and Neural Networks. It proceeds to offer an in-depth treatment of Convolutional neural networks(CNN) and deep machine learning. It also covers various architecture optimization techniques including data optimization, dropouts,layer patterns and sizing. It provides CNN visualization and a comprehensive case study of recent CNN architectures including AlexNet, ZFNet and GoogleNet.
Biography:
Dr. Kiran Gunnam is working as a technical director of algorithms and signal processing at Velodyne LiDAR, Inc. He is leading the development of machine learning, simultaneous localization and mapping (SLAM) and signal processing algorithms and real-time hardware implementation for LiDAR sensor based self-driving cars.
Dr. Gunnam is an innovative technology leader with vision and passion who effectively connects with individuals and groups. Dr. Gunnam's breakthrough contributions are in the areas of advanced error correction systems, storage class memory systems and vision based navigation systems. He has helped drive organizations to become industry leaders through ground-breaking technologies. Dr. Gunnam has 70 issued patents and 100+ patent applications/invention disclosures on algorithms, computing and storage systems. He is the lead inventor/sole inventor for 90% of them. Dr. Gunnam’s patented work has been already incorporated in more than 2 billion data storage and WiFi chips and is set to continue to be incorporated in more than 500 million chips per year.
Dr. Gunnam served as IEEE Distinguished Speaker and Plenary Speaker for 20+ events and international conferences and more than 2000 attendees in USA, Canada and Asia benefited from his lecture talks. He also teaches graduate level course focused on machine learning systems at Santa Clara University.
Email:
Kiran Gunnam of Velodyne Lidar Inc
Convolutional Neural Networks and Deep Machine learning
Biography:
Email:
Address:United States
Agenda
- Brief Overview of Machine Learning and Neural Networks
- In-depth treatment of CNN and Deep Machine Learning
- Architecture Optimization Techniques – Data Optimization, Drop Outs, Layer Patterns, Sziing
- Comprehensive case Study on AlexNet, ZFNet, GoogleNet
In Collaboration with IEEE Computer Society, Computational Intelligence Society and IIIT IEEE Student Branch