Castuner

Satellite image deep learning

Robin Cole

Dive into the world of deep learning for satellite images with your host, Robin Cole. Robin meets with experts in the field to discuss their research, products, and careers in the space of satellite image deep learning. Stay up to date on the latest trends and advancements in the industry - whether you’re an expert in the field or just starting to learn about satellite image deep learning, this a podcast for you. Head to https://www.satellite-image-deep-learning.com/ to learn more about this fascinating domain www.satellite-image-deep-learning.com

Podcast website

Listen in your app

Episodes

49 episodes

  1. Benchmarking AI for Critical Infrastructure Mapping 30:54
  2. Building Open GeoAI for Humanitarian Response 25:36
  3. Ai Agents with Hyades & BlazerOps 20:37
  4. Building OlmoEarth: AI2’s Open Foundation Model for Satellite Imagery 36:44
  5. A Single GPU Is All You Need for Self-Supervised Pretraining 32:39
  6. Mapping The World at Taylor Geospatial 34:01
  7. BetaEarth: Open Embeddings of Sentinel-2 and Sentinel-1 with a Little Help of AlphaEarth 26:15
  8. Geospatial Annotation with LabelMe and Segment Anything 11:36
  9. Mapping South America and Beyond with Fields of The World V2 30:31
  10. State Of The Art Object Detection 30:18
  11. Tessera: A Temporal Foundation Model for Earth Observation 23:30
  12. AutoML for Spaceborne AI 20:08
  13. Methane Plume Detection with AutoML 16:31
  14. Democratising access to GeoAI with InstaGeo 23:09
  15. PhiDown: Fast, Simple Access to Copernicus Data 9:15
  16. Chained Models for High-Res Aerial Solar Fault Detection 34:15
  17. TorchGeo 1.0 with Adam Stewart 28:58
  18. Challenges and opportunities for Ai mapping 23:17
  19. Solar Panel Detection with Satellite Imagery 31:04
  20. Chat2Geo and the Power of LLMs 21:44
  21. OmniCloudMask 18:58
  22. Planetixx competition approach 29:23
  23. IceCloudNet and the PhD Journey 27:05
  24. Insights from the SMAC earthquake detection challenge 27:11
  25. Building Damage Assessment 17:10
  26. Deepness QGIS plugin 12:57
  27. The FLAIR land cover mapping challenge 18:58
  28. Meta-learning with Meteor 15:31
  29. Uncertainty Quantification for Neural Networks with Pytorch Lightning UQ Box 25:36
  30. Field boundary detection with Segment Anything 18:34
  31. Interpretable Deep Learning 21:08
  32. Earthquake detection with Sentinel-1 20:17
  33. Machine learning with SAR at ASTERRA 24:26
  34. Major TOM: Expandable EO Datasets 26:19
  35. Location Embedding with SatCLIP, with Konstantin Klemmer 25:11
  36. AI powered image annotation with James Gallagher 23:58
  37. Deep learning for 3D understanding of satellite images 1:41:44
  38. Deep learning in Google Earth Engine with Jake Wilkins 31:19
  39. PyRawS for onboard image processing with Roberto Del Prete 31:25
  40. Synthetic training data with Nathan Kundtz 19:58
  41. Orbuculum with Derek Ding 12:00
  42. The machine learning workflow at Development Seed with Ryan Avery 28:30
  43. AI at Nearmap with Michael Bewley 24:11
  44. Career chat with Martha Morrisey 9:18
  45. Satellite image time series with Gilberto Camara 29:42
  46. Career chat with Nishant Yadav 15:57
  47. Vision Transformers for Satellite Image Time Series with Michail Tarasiou 10:48
  48. Career chat with Zhuang-Fang NaNa Yi 13:22
  49. Career chat with Philip Robinson 12:37