May ’23 Computer Vision Meetup – APAC
May 25, 2023 – 10AM IST / 04:30 UTC
May 25, 2023: 10AM IST (04:30 UTC)
Virtual / Zoom
- Wildlife Watcher: A Smart Wildlife Camera – Victor Anton, Founder and CEO of Wildlife.ai
- Applying Computer Vision to Real Estate at Opendoor – Shashwat Srivastava, Sr. Software Engineer, Opendoor
- YOLO-NAS: SOTA Object Detection Generated by NAS – Eugene Khvedchenia, Deep Learning Engineer, Deci AI
- Closing Remarks
Wildlife Watcher: A Smart Wildlife Camera
Wildlife conservation is more critical now than ever, and monitoring biodiversity is key to protecting our planet. Wildlife.ai, an environmental non-profit, is using cutting-edge technology like artificial intelligence, computer vision and community collaboration to help biodiversity conservation. Their Wildlife Watchers program combines open-source, low-powered cameras with user-friendly software to make conservation accessible to everyone.
Victor Anton is Founder and CEO of Wildlife.ai, Victor is a wildlife biologist who works with research institutions, governments and communities around the world to translate data into improved conservation practices.
Applying Computer Vision to Real Estate at Opendoor
This talk will dive into the the many applications of computer vision in the real estate sector. Real estate is one of the few industries which still uses tools from the 2000s and can stand to benefit greatly from the advances in machine learning. In this talk, we will deep dive into Enricher – a computer vision pipelines which helps Opendoor conduct virtual assessments of homes across the country at scale. In addition, we will also discuss some high level computer vision projects being worked on at Opendoor.
Shashwat Srivastava is a Senior Engineer on the Data Platform team at Opendoor. Opendoor is a real estate company which greatly simplifies the process of buying and selling your home. Over the 5 years, Shashwat worked on Data and Analytics at Opendoor on everything from data infrastructure to ETL pipelines to building backend services for real time serving of data. Before this role, he was a backend engineer at AppDynamics which he joined right after his undergrad at Carnegie Mellon.
YOLO-NAS: SOTA Object Detection Generated by NAS
Deci.ai is thrilled to announce the release of a new object detection model, YOLO-NAS. This model is a game-changer in the world of object detection, providing superior real-time object detection capabilities and production-ready performance. Eugene will discuss the new model, and the hardware-aware NAS approach.
Eugene Khvedchenia is a Deep Learning Engineer at Deci AI.
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