Remote Sensing
SI-STSAR-7 is a labeled spatiotemporal dataset for sea ice classification based on SAR images. The dataset is produced from 80 Sentinel-1 A/B SAR scenes during the two freezing periods of Hudson Bay from October 2019 to May 2020 and from October 2020 to April 2021, which are provided by the Copernicus Open Access Center. The Sentinel-1 SAR images were preprocessed with noise reduction and incidence angle dependence correction before use.
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<p>This is the image dataset for satellite image processing which is a collection therml infrared and multispectral images .</p>
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The data provided corresponds to the open-source codes and reference images from a computer interface for real-time gait biofeedback using a Wearable Integrated Sensor System for Data Acquisition.
This data is the supplmementary material of the publication I. Sanz-Pena, J. Blanco and J. H. Kim, "Computer Interface for Real-Time Gait Biofeedback Using a Wearable Integrated Sensor System for Data Acquisition," in IEEE Transactions on Human-Machine Systems, https://doi.org/10.1109/THMS.2021.3090738
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[NEW] Urb3DCD V2 is now avalaible!
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The proposed dataset, termed PC-Urban (Urban Point Cloud), is captured with an Ouster LiDAR sensor with 64 channels. The sensor is installed on an SUV that drives through the downtown of Perth, Western Australia (WA), Australia. The dataset comprises over 4.3 billion points captured for 66K sensor frames. The labelled data is organized as registered and raw point cloud frames, where the former has a different number of registered consecutive frames. We provide 25 class labels in the dataset covering 23 million points and 5K instances.
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The SPYSTUF hyperspectral data contains high spatial and spectral resolution Aisa Eagle II (visible to near infrared, 400-900 nm) airborne imaging spectrometer above a Hyytiälä forest research station hosting the SMEAR II (Station for Measuring Ecosystem-Atmosphere Relations, 61°50' N, 24°17' E) on 3 July 2015. The spectral resolution of the data is 4.6 nm, and the spatial resolution 0.6 m.
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WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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1344 Views
WITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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419 ViewsWITH the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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272 Views
With the advancement in sensor technology, huge amounts of data are being collected from various satellites. Hence, the task of target-based data retrieval and acquisition has become exceedingly challenging. Existing satellites essentially scan a vast overlapping region of the Earth using various sensing techniques, like multi-spectral, hyperspectral, Synthetic Aperture Radar (SAR), video, and compressed sensing, to name a few.
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285 Views