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المحتوى المقدم من tinyML Foundation and TinyML Foundation. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة tinyML Foundation and TinyML Foundation أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.
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Revolutionizing Nano-UAV Technology with Cutting-Edge On-Device Learning Strategies

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Manage episode 446045882 series 3574631
المحتوى المقدم من tinyML Foundation and TinyML Foundation. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة tinyML Foundation and TinyML Foundation أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

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Unlock the secrets of edge computing and on-device learning with Elias Cereda, a trailblazing PhD student at the Dalle Molle Institute for Artificial Intelligence in Italy, as we explore the transformative potential of AI in nano-UAV technology. Discover how Elias is pioneering solutions to the challenges of domain shifts in AI models, particularly those trained in simulations and deployed in real-world scenarios. From enhancing privacy and security through on-device learning to mastering the intricacies of human pose estimation for autonomous navigation, this episode is a treasure trove of insights. We dive into the practicalities of deploying systems using the Crazyflie 2.1 drone alongside GreenWaves' sophisticated RISC-V GAP8 and GAP9 chips, all while managing tight power constraints.
Take a closer look at the complexities of on-device and online learning with Elias as we delve into the nuances of continual learning. Learn how maintaining a balance between retaining previous knowledge and integrating new data is crucial in the field. Elias introduces us to a self-supervised metric that operates without initial labels, cleverly utilizing odometry data to refine model predictions. By considering human movement as measurement noise and refining data through post-processing techniques, the episode unveils strategies to enhance model performance without explicit tracking.
For those eager to delve deeper into the methodologies discussed, Elias points to a comprehensive paper that promises to enrich your understanding of this cutting-edge technology.

Learn more about the tinyML Foundation - tinyml.org

  continue reading

فصول

1. Revolutionizing Nano-UAV Technology with Cutting-Edge On-Device Learning Strategies (00:00:00)

2. On-Device Learning for Nano-UAVs (00:00:09)

3. Implementing Continual Learning for Nano-UAVs (00:19:03)

9 حلقات

Artwork
iconمشاركة
 
Manage episode 446045882 series 3574631
المحتوى المقدم من tinyML Foundation and TinyML Foundation. يتم تحميل جميع محتويات البودكاست بما في ذلك الحلقات والرسومات وأوصاف البودكاست وتقديمها مباشرة بواسطة tinyML Foundation and TinyML Foundation أو شريك منصة البودكاست الخاص بهم. إذا كنت تعتقد أن شخصًا ما يستخدم عملك المحمي بحقوق الطبع والنشر دون إذنك، فيمكنك اتباع العملية الموضحة هنا https://ar.player.fm/legal.

Send us a text

Unlock the secrets of edge computing and on-device learning with Elias Cereda, a trailblazing PhD student at the Dalle Molle Institute for Artificial Intelligence in Italy, as we explore the transformative potential of AI in nano-UAV technology. Discover how Elias is pioneering solutions to the challenges of domain shifts in AI models, particularly those trained in simulations and deployed in real-world scenarios. From enhancing privacy and security through on-device learning to mastering the intricacies of human pose estimation for autonomous navigation, this episode is a treasure trove of insights. We dive into the practicalities of deploying systems using the Crazyflie 2.1 drone alongside GreenWaves' sophisticated RISC-V GAP8 and GAP9 chips, all while managing tight power constraints.
Take a closer look at the complexities of on-device and online learning with Elias as we delve into the nuances of continual learning. Learn how maintaining a balance between retaining previous knowledge and integrating new data is crucial in the field. Elias introduces us to a self-supervised metric that operates without initial labels, cleverly utilizing odometry data to refine model predictions. By considering human movement as measurement noise and refining data through post-processing techniques, the episode unveils strategies to enhance model performance without explicit tracking.
For those eager to delve deeper into the methodologies discussed, Elias points to a comprehensive paper that promises to enrich your understanding of this cutting-edge technology.

Learn more about the tinyML Foundation - tinyml.org

  continue reading

فصول

1. Revolutionizing Nano-UAV Technology with Cutting-Edge On-Device Learning Strategies (00:00:00)

2. On-Device Learning for Nano-UAVs (00:00:09)

3. Implementing Continual Learning for Nano-UAVs (00:19:03)

9 حلقات

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