** Ad-free episodes are available to our paid supporters over at patreon.com/geeks ** Host David Barr Kirtley, author of the book Save Me Plz and Other Stories, talks geek culture with guests such as Neil Gaiman, George R. R. Martin, Richard Dawkins, Simon Pegg, Bill Nye, Margaret Atwood, Neil deGrasse Tyson, and Ursula K. Le Guin. Geek’s Guide to the Galaxy has appeared on recommended podcast lists from NPR, The Guardian, Wired, The A.V. Club, BBC America, CBC Radio, WVXU, io9, Omni, The St ...
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1 100 Episodes WASTED! Fix These 4 Simple Podcast Blunders in Minutes 14:42
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Is your health and wellness podcast optimized for success, or are crucial oversights holding back your potential? I audited a doctor’s podcast recently and was shocked at what I found. This podcast had over 100 episodes—pretty impressive. However, the whole setup of the podcast had some brutal mistakes that I’m sure were holding this doctor back from seeing bigger results. How can optimizing your podcast's website links transform your show's reach? Are you missing out on SEO benefits that could elevate your visibility? Curious about the impact of professional collaboration on your podcast? Don't let simple mistakes hold you back. Tune in to find out how to turn your podcast into a lead-generating powerhouse! Today’s episode includes: How minor mistakes hinder podcast growth and engagement. Why directing podcast episode links on Apple, Spotify, etc to your own website is ideal. Why collaborating with professional teams can elevate your podcast impact and revenue. How maintaining high production standards enhances credibility, especially in the health and wellness space. How omitting crucial subscription links will limit your audience growth. Why owning a proper domain ensures long-term SEO benefits and authority with search engines. How missing social media links in your show notes makes it difficult for listeners to connect with you. Why understanding and avoiding common mistakes ensures maximum ROI from podcasting efforts. Are you pouring your heart into your podcast but still not seeing the growth you deserve? Download our free guide to unlock your podcast’s full potential and expand your impact: https://eastcoaststudio.com/5mistakes Our LinkedIn: https://www.linkedin.com/company/eastcoaststudio/ Our Instagram: https://www.instagram.com/ecpodcaststudio/…
#14 The Azavea Dialogues, Pt 3: Utilizing Unique Geospatial Data for Deep Learning
Manage episode 245236385 series 2492216
Content provided by CosmiQ Works. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CosmiQ Works or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
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30 episodes
Manage episode 245236385 series 2492216
Content provided by CosmiQ Works. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CosmiQ Works or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.
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×Founded in 2015 as part of IQT Labs, CosmiQ Works launched to focus on the geospatial analytics market and provide technical insights, targeted research, reports, and more. Over the past six years CosmiQ has produced many projects and insights that have helped the intelligence and academic communities better understand how geospatial can help tackle hard problems. Our final Training_Data podcast brings together CosmiQ's current colleagues and alum in a special episode celebrating the team's key accomplishments, milestones, and lessons learned through the years.…

1 #28 Introducing the SpaceNet 7 Challenge: Multi-Temporal Urban Development 50:54
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Satellite imagery analytics have numerous human development and disaster response applications, particularly when time series methods are involved. The Multi-Temporal Urban Development SpaceNet 7 Challenge focuses on developing novel computer vision methods for non-video time series data, asking participants to identify and track buildings in satellite imagery time series collected over rapidly urbanizing areas. In this episode, CosmiQ’s Ryan Lewis, Adam Van Etten, and Daniel Hogan are joined by Planet’s Jesus Martinez Manzo and AWS Disaster Response’s Grace Kitzmiller to explore this new challenge. Learn more at www.spacenet.ai , and at the DownLinQ ( https://medium.com/the-downlinq )…

1 #27 SpaceNet 6: The Multi-Modal Extravaganza Family Hour 36:15
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CosmiQ’s Jake Shermeyer and Daniel Hogan are joined by Capella Space’s Jason Brown and IEEE Geoscience and Remote Sensing’s (GRSS) Ronny Hänsch to once again discuss the SpaceNet 6 Dataset and post-challenge experiments. Learn more about data fusion and deep learning approaches that work to blend synthetic aperture radar (SAR) and optical imagery. Additionally, the podcast also explores the value of frequent SAR revisits that can be beneficial for foundational mapping applications. Finally, the group discusses CosmiQ’s new addition to the Solaris python package: a multi-modal pre-processing library and a new API called ‘PipeSegment’ for seamlessly stringing together different operations. SpaceNet is a nonprofit made possible by co-founder and managing partner, CosmiQ Works; co-founder and co-chair, Maxar Technologies; and all the other Partners: Amazon Web Services (AWS), Capella Space, Topcoder, IEEE Geoscience and Remote Sensing (GRSS), the National Geospatial-Intelligence Agency, and Planet.…

1 #26 SpaceNet 6 Challenge Results: Multi-Sensor All-Weather Mapping 38:43
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SpaceNet is a non-profit dedicated to accelerating open source, applied research in geospatial machine learning. In this episode, CosmiQ’s Ryan Lewis, Jake Shermeyer, and Daniel Hogan discuss the SpaceNet 6 Challenge where participants were asked to automatically extract building footprints with computer vision and AI algorithms using a combination of synthetic aperture radar (SAR) and electro-optical imagery. Hear about the challenge’s winning artificial intelligence models and the tradeoff between inference speed and model performance. SpaceNet is made possible by co-founder and managing partner, CosmiQ Works; co-founder and co-chair, Maxar Technologies; and all the other Partners: Amazon Web Services (AWS), Capella Space, Topcoder, IEEE Geoscience and Remote Sensing (GRSS), the National Geospatial-Intelligence Agency, and Planet. Learn more at www.spacenet.ai , and at the DownLinQ ( https://medium.com/the-downlinq )…

1 #25 Evaluating SpaceNet 5 Challenge Results: Road Network Detection & Optimized Routing 54:14
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Despite its application to myriad humanitarian and civil use cases, automated road network extraction from overhead satellite imagery remains quite challenging. However, the SpaceNet 5 challenge made significant progress in this field with top participants being able to extract both road networks and speed/travel time estimates for each roadway. On today’s pod, CosmiQ’s Ryan Lewis and Dr. Adam Van Etten explore the challenge’s unique dataset and geographic diversity over time, the winning models, and the tradeoff between inference speed and model performance. SpaceNet is a non-profit LLC co-founded and managed by In-Q-Tel's CosmiQ Works in collaboration Maxar Technologies, a co-founder, and the other SpaceNet Partners including AWS, Intel AI, Topcoder, Capella Space, IEEE GRSS, The National Geospatial-Intelligence Agency (NGA), and Planet.…
How can lessons from geospatial computer vision applications impact bio image analysis? CosmiQ’s Dr. Nick Weir and B.Next’s Dr. Dylan George explore the intersection of these two fields and why artificial intelligence (AI) has struggled to gain traction with both satellite imagery and medicine. Hear about their project that researched similarities and differences between satellite imagery, microscopy, and “normal” photographs, and why researchers developing AI methods for microscopy might want to leverage the work done for geospatial applications. Read more about their project at The DownLinQ and BioQuest : · Viewing the World Through a Straw, Part 1 · Viewing the World Through a Straw, Part 2…

1 #23 Into the Gray Zone: Emerging Technology’s Role in the Geopolitical Landscape 40:00
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1 #22 Machine Learning Robustness Study: Building Out an Increasingly Diverse Dataset 29:22
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1 #21 Announcing SpaceNet® 6: Multi-Sensor All Weather Mapping 41:47
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1 #19 Implementing AI Projects: Lessons Learned & Emerging Trends 38:23
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1 #18 Contributing to Open Source Through Hacktoberfest 38:37
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1 #17 Geospatial Analytics for the Masses with CARTO 44:56
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1 #16 Venture Capital Investing in Commercial Space & Beyond 43:52
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1 #14 The Azavea Dialogues, Pt 3: Utilizing Unique Geospatial Data for Deep Learning 35:35
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1 #13 The Azavea Dialogues, Pt 2: Building a Business with Open Source Software 38:40
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1 #12 The Azavea Dialogues, Pt 1: AI’s Impact on Geospatial 50:21
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1 #11 SpaceNet Partners Unite: Building an Open Source Initiative Pt. 2 30:01
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1 #10 SpaceNet Partners Unite: Building an Open Source Initiative Pt. I 37:55
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1 #9 Analyzing Times Series Data for Humanitarian Response 31:46
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1 #8 Introducing Solaris: CosmiQ’s Open Source Python Library for AI 25:12
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1 #7 Are We There Yet? Announcing SpaceNet 5: Roads, Routes, & Travel Times 25:21
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1 #6 Enabling Analytics (+ Security) at the Edge 46:00
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1 #5 Data Science, Open Source, and All That: A Conversation with Anaconda 50:07
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Peter Wang, CTO and Co-Founder of Anaconda sits down with Ryan Lewis, Adam Van Etten, and Coley Lewis to talk about open source software and its role for both data science applied research as well as product development and deployment.
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1 #4 Analysis at All Angles: SpaceNet 4 and Off Nadir Imagery 38:51
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1 #3 Enhance That: Super Resolution & Object Detection 26:55
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Adam Van Etten, Jake Shermeyer, and Ryan Lewis discuss CosmiQ's year long project studying the impact of image super resolution on object detection model performance.
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Adam Van Etten, CosmiQ's Director of Research, and David Lindenbaum, formerly CosmiQ's Principal Engineer, talk about the SpaceNet 3 Challenge: Road network extract and routing from a single satellite image.
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