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Presentation
Media
Abstract:
Learn how recent advances in AI can be used to map informal settlements, or slums, in developing countries. We'll show how slums can be mapped using machine learning with noisy annotations and multi-resolution, multi-spectral data. We'll discuss an effective end-to-end framework that detects and maps the locations of informal settlements using low-resolution, freely available Sentinel-2 satellite imagery. Our talk will examine different approaches based on multi-spectral information to identify roofing material types and show how our work can be used for slums all over the world. We'll also describe how multi-spectral, multi-resolution and multi-temporal satellite imagery can be used during natural disasters to quantify the impact on urban infrastructure. This session presents research undertaken in the NASA and ESA Frontier Development Lab.
Learn how recent advances in AI can be used to map informal settlements, or slums, in developing countries. We'll show how slums can be mapped using machine learning with noisy annotations and multi-resolution, multi-spectral data. We'll discuss an effective end-to-end framework that detects and maps the locations of informal settlements using low-resolution, freely available Sentinel-2 satellite imagery. Our talk will examine different approaches based on multi-spectral information to identify roofing material types and show how our work can be used for slums all over the world. We'll also describe how multi-spectral, multi-resolution and multi-temporal satellite imagery can be used during natural disasters to quantify the impact on urban infrastructure. This session presents research undertaken in the NASA and ESA Frontier Development Lab.  Back
 
Topics:
AI Application Deployment and Inference, AI and DL Research, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2019
Session ID:
S9362
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Abstract:
Recent advances in earth observation are opening up a new exciting area for exploration of satellite image data. We'll teach you how to analyse this new data source with deep neural networks. Focusing on emergency response, you will learn how to apply deep neural networks for semantic segmentation on satellite imagery. We will specifically focus on multimodal segmentation and the challenge of overcoming missing modality information during inference time. It is assumed that registrants are already familiar with fundamentals of deep neural networks.
Recent advances in earth observation are opening up a new exciting area for exploration of satellite image data. We'll teach you how to analyse this new data source with deep neural networks. Focusing on emergency response, you will learn how to apply deep neural networks for semantic segmentation on satellite imagery. We will specifically focus on multimodal segmentation and the challenge of overcoming missing modality information during inference time. It is assumed that registrants are already familiar with fundamentals of deep neural networks.  Back
 
Topics:
AI and DL Research, Advanced AI Learning Techniques (incl. GANs and NTMs)
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8596
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Abstract:

Recent advances in earth observation are opening up a new exciting area for exploration of satellite image data. In this session you will learn how to analyse this new data source with deep neural networks. Focusing on Emergency Response, you will learn (1) how to apply deep neural networks for Semantic Segmentation on satellite imagery. Additionally, we present recent advances of the Multimedia Satellite Task at MediaEval 2017 and show (2) how to extract and fuse content of natural disasters from Satellite Imagery and Social Media Streams. It is assumed that registrants are already familiar with fundamentals of deep neural networks.

Recent advances in earth observation are opening up a new exciting area for exploration of satellite image data. In this session you will learn how to analyse this new data source with deep neural networks. Focusing on Emergency Response, you will learn (1) how to apply deep neural networks for Semantic Segmentation on satellite imagery. Additionally, we present recent advances of the Multimedia Satellite Task at MediaEval 2017 and show (2) how to extract and fuse content of natural disasters from Satellite Imagery and Social Media Streams. It is assumed that registrants are already familiar with fundamentals of deep neural networks.

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Topics:
Other
Type:
Talk
Event:
GTC Europe
Year:
2017
Session ID:
23479
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