Thank you for attending the October 30, 2018 webinar "Architecting Always-On, Context-Aware, On-Device AI Using Flexible Low-power FPGAs," presented by Deepak Boppana, Lattice Semiconductor's Senior Director of Marketing, and Gordon Hands, the company's Marketing Director for IP and Solutions, and organized by the Embedded Vision Alliance!
For more information on Lattice Semiconductor's sensAI stack, please visit www.latticesemi.com/sensAI.
For more information on deep learning for embedded vision and other computer vision topics, please visit the Embedded Vision Alliance website at https://www.embedded-vision.com. You'll particularly find the following articles to be of interest:
- Using Convolutional Neural Networks for Image Recognition
- Software Frameworks and Toolsets for Deep Learning-based Vision Processing
- Implementing Vision with Deep Learning in Resource-constrained Designs
- Data Sets for Machine Learning Model Training
- Solving Intelligence, Vision and Connectivity Challenges at the Edge with ECP5 FPGAs
as well as the following recent presentations from Lattice Semiconductor:
- Programmable CNN Acceleration in Under 1 Watt
- Machine Learning Inference In Under 5 mW with a Binarized Neural Network on an FPGA
- Deep Quantization for Energy Efficient Inference at the Edge
and recent demonstrations from the company:
- The Expanded sensAI Stack
- Human Presence Detection at the Edge
- Object Counting Using ECP5 and Machine Learning
- Speed Sign Detection Using ECP5 and Machine Learning
- A Deep Neural Network that Consumes Only ~800 uW
- Vision Applications for Collision Avoidance and Face/Object Tracking
- The Embedded Vision Development Kit for Low-power Applications at the Edge
- Low-power Hardware and Software Face Detection Implementations
Subscribe to the Alliance's site-wide RSS feed, along with its Facebook, Google+, LinkedIn Company, LinkedIn Group and Twitter social media channels, to receive notification whenever new deep learning and other vision processing content is published on the Alliance website. We also encourage you to register on the website, which offers tutorial articles, videos, code downloads and a discussion forum staffed by technology experts, among other benefits.
The Embedded Vision Academy area of the website provides in-depth technical training and other resources to help product creators integrate visual intelligence into next-generation software and systems. Course material in the Embedded Vision Academy spans a wide range of vision-related subjects. Registered website users can also receive the Embedded Vision Alliance’s twice-monthly email newsletter, Embedded Vision Insights, among other benefits.
Embedded Vision Summits are technical educational forums for product creators interested in incorporating visual intelligence into electronic systems and software. They provide how-to presentations, inspiring keynote talks, demonstrations, and opportunities to interact with technical experts from Embedded Vision Alliance member companies. These events are intended to inspire attendees' imaginations about the potential applications for practical computer vision technology through exciting presentations and demonstrations, to offer practical know-how for attendees to help them incorporate vision capabilities into their hardware and software products, and to provide opportunities for attendees to meet and talk with leading vision technology companies and learn about their offerings.
For the set of presentations from the May 2018 Embedded Vision Summit, along with a growing listing of published demonstration and presentation videos from the event, check out the event Replay page. Replay pages from prior Summits are listed below:
The next Embedded Vision Summit, along with accompanying workshops, will take place on May 20-23, 2019 in Santa Clara, California. Please reserve a spot on your calendar and plan to attend. More information on next year's Summit, including online registration, will be available soon on the Alliance website.
Finally, the link to a complimentary copy of the slide deck from this webinar is below:
- October 30, 2018 Webinar.pdf (2.2 MByte PDF)