Satellite image deep learning

In this episode, I caught up with Nils Lehmann to learn about Uncertainty Quantification for Neural Networks. The conversation begins with a discussion on Bayesian neural networks and their ability to quantify the uncertainty of their predictions. Unlike regular deterministic neural networks, Bayesian neural networks offer a more principled method for providing predictions with a measure of confid...

In this episode I caught up with Samuel Bancroft to learn about segmenting field boundaries using Segment Anything , aka SAM. SAM is a foundational model for vision released by Meta, which is capable of zero shot segmentation. However there are many open questions about how to make use of SAM with remote sensing imagery. In this conversation, Samuel describes how he used SAM to perform segmentatio...

In this episode I caught up with Yotam Azriel to learn about interpretable deep learning. Deep learning models are often criticised for being "black box" due to their complex architectures and large number of parameters. Model interpretability is crucial as it enables stakeholders to make informed decisions based on insights into how predictions were made. I think this is an important topic and I...

In this episode I caught up with Daniele Rege Cambrin, to learn about Earthquake detection with Sentinel-1 (SAR) images. Daniele has a key role in organising a new competition on this task, SMAC: Seismic Monitoring and Analysis Challenge. The topics covered include the logistics of organising this competition, and the lessons Daniele learned from organising a previous one. You can also view the re...

In this episode Robin catches up with Inon Sharony to learn about the fascinating world of machine learning with SAR imagery. The unique attributes of SAR imagery, such as its intensity, phase, and polarisation, provide rich information for deep learning models to learn features from. The discussion covers the innovative applications ASTERRA is developing, and the nuances of machine learning with...

In this episode, Robin catches up up with Alistair Francis and Mikolaj Czerkawski to learn about Major TOM, which is a significant new public dataset of Sentinel 2 imagery. Noteworthy for its immense size at 45 TB, Major TOM also introduces a set of standards for dataset filtering and integration with other datasets. Their aim in releasing this dataset is to foster a community-centred ecosystem of...

In this video Robin catches up with Konstantin Klemmer to discus SatClip, which is a new global & general purpose location encoder trained on Sentinel 2 imagery. The conversation covered the training of encoders such as CLIP, and discussed the implications for downstream applications. Note you can also view the video of this recording on YouTube here * Konstantin on LinkedIn * SatCLIP Bio: Konstan...

In this episode Robin catches up with James Gallagher to learn about the latest AI innovations reshaping image annotation. The conversation covered significant new models such as Segment Anything, GroundingDINO and RemoteCLIP , and discussed how these models can be linked together to enable new annotation capabilities. Note you can also view the video of this recording on YouTube here * James on L...

A large fraction of acquired satellite images contain 2D projections of Earth. However, for many downstream applications, 3D understanding is beneficial or necessary. In recent years, deep learning has enabled a number of solutions for learning 3D representations from 2D satellite images . This episode delivers an overview of some of the prominent works in this area. Mikolaj hosts 3 guests: Dawa D...

In this episode Robin catches up with Jake Wilkins to learn about Deep learning in Google Earth Engine. Jake has been building commercial Earth Engine applications for the past three years and in this conversation he describes the pros and cons of several approaches to using deep learning models with Earth Engine. Note you can also view the video of this recording on YouTube here * Jake on LinkedI...

In this episode Robin catches up with Roberto Del Prete to learn about PyRaws. PyRaws is a powerful open source Python package that provides a comprehensive set of tools for working with Sentinel 2 raw imagery. It provides tools for band coregistration, geo-referencing, data visualisation, and image processing. What is particularly exciting is that this software could be deployed onto future satel...

In this episode Robin catches up with Nathan Kundtz to learn about the creation, and use of synthetic image data in training machine machine models. Nathan has a PhD in physics, and over 40 peer reviewed papers and 15 patents to his name. As a serial entrepreneur, he has successfully founded multiple companies and raised over $250 million in venture capital funding. Note you can also view the vide...

In the episode I caught up with the co-founder of the company developing Orbuculum, Derek Ding, to learn more about this innovative new platform. What makes Derek's story even more intriguing is that he doesn't have a traditional background in remote sensing. However, fuelled by ambition and a desire to introduce new technologies, he is determined to transform the landscape of the Earth observatio...

In this episode, Robin catches up with Ryan Avery to learn about the machine learning workflow at Development Seed. The making of this episode was inspired by a three part blog series Ryan has authored on the ML tooling stack used at Development Seed. Please note the video is also available on YouTube - https://developmentseed.org/blog/2023-04-13-ml-tooling-3 - https://www.linkedin.com/in/ryan-ave...

In this video, Robin catches up with Michael Bewley to hear about the use of AI at Nearmap. Nearmap captures very high resolution aerial imagery and Michael and his team have trained a single segmentation model to identify 78 different target layers in the imagery. These layers can then be displayed on a map or accessed via an API. Please note the video is also available on YouTube * Michael on Li...

Join Robin in a career chat with Martha Morrisey, a senior machine learning engineer at Pachama, a company elevating remote sensing data and machine learning to fight climate change by monitoring carbon capture and storage projects in forests. In this episode, Martha shares her career journey and provides further insight into the role of a machine learning engineer. * Martha on LinkedIn * Pachama...

In this episode, Robin catches up with Gilberto Camara to talk about SITS. SITS is an open-source R package for land use and land cover classification of big Earth observation data using satellite image time series. Gilberto is a Senior Researcher in GIScience, Geoinformatics, Spatial Data Science and Land Use Change at Brazil’s National Institute for Space Research. * https://github.com/e-sensing...

In this career chat, Robin catches up with Nishant Yadav to hear about his path from PhD to Applied Scientist (II) at Microsoft Azure AI working on computer vision. Nishant graduated from Northeastern University in Boston, US, with a Ph. D. in machine learning with applications in environmental and climate science. His research focused on developing deep transfer learning methods for extracting in...

In this episode, Robin catches up with Michail Tarasiou to discuss the new paper, ViTs for SITS: Vision Transformers for Satellite Image Time Series. This paper introduces the temporo-spatial vision transformer (TSViT) architecture. The TSViT incorporates novel design choices that make it suitable for time series tasks such as crop classification. In this work, TSViT crop classification and segmen...

In this episode of the career chat series, Robin catches up with Zhuang-Fang NaNa Yi to hear about her career path into the role of senior machine learning engineer at Regrow Ag * https://www.linkedin.com/in/zhuang-fang-yi-phd-01178a34/ * https://www.regrow.ag/ Bio: Zhuang-Fang NaNa Yi is a senior machine learning engineer at Regrow Ag. Her day-to-day work involves building R&D and machine learnin...

In this podcast, Robin catches up with Philip Robinson to discuss his career path, and hear how he transitioned from working in computer security research, to working on environmental and satellite imaging challenges at the Global Fishing Watch. - https://www.linkedin.com/in/philip-robinson-2878642a/ - https://globalfishingwatch.org/ Bio: Philip Robinson is a Scientific Programmer at Global Fishin...