SR
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All models matching “SR”Datasets
All datasets matching “SR”srtm30m-ozt2-v2
SRTM 30m OZT2 Elevation Tiles
This dataset contains SRTM 30-meter resolution elevation data encoded in the OZT2 tile format.
Format
OZT2 is a high-performance elevation tile format:
Compression: ~93% smaller than Terrarium PNG
Prediction: Gradient-based prediction (left neighbor + vertical gradient)
Quantization: Adaptive bit-depth (8/10/12/16-bit per channel)
Codec: Zstd q3 (30× faster encode than Brotli, same decode speed)
Each tile is 256×256 pixels in Web… See the full description on the dataset page: https://huggingface.co/datasets/aliasfox/srtm30m-ozt2-v2.TFUScapes
tags:
- medical
pretty_name: tfuscapes
task_categories:
- other
language:
- en
size_categories:
- 1K<n<10K
modalities:
- npz
A Skull-Adaptive Framework for AI-Based 3D Transcranial Focused Ultrasound Simulation
Vinkle Srivastav, Juliette Puel, Jonathan Vappou, Elijah Van Houten, Paolo Cabras*, Nicolas Padoy*
*co-last authors
Access the paper
Introduction
Transcranial focused ultrasound (tFUS) is an emerging modality for non-invasive… See the full description on the dataset page: https://huggingface.co/datasets/vinkle-srivastav/TFUScapes.MapPool
MapPool - Bubbling up an extremely large corpus of maps for AI
MapPool is a dataset of 75 million potential maps and textual captions. It has been derived from CommonPool, a dataset consisting of 12 billion text-image pairs from the Internet. The images have been encoded by a vision transformer and classified into maps and non-maps by a support vector machine. This approach outperforms previous models and yields a validation accuracy of 98.5%. The MapPool dataset may help to train… See the full description on the dataset page: https://huggingface.co/datasets/sraimund/MapPool.srtm30m-mergedlatent-sr-embeddings
Latent-SR Embeddings: Precomputed VAE Latents for Medical Image Super-Resolution
Precomputed VAE latent embeddings from the paper:
"Domain-Specific Latent Representations Improve the Fidelity of Diffusion-Based Medical Image Super-Resolution"Sebastian Cajas, Ashaba Judith, Rahul Gorijavolu, Sahil Kapadia, Hillary Clinton Kasimbazi, Leo Kinyera, Emmanuel Paul Kwesiga, Sri Sri Jaithra Varma Manthena, Luis Filipe Nakayama, Ninsiima Doreen, Leo Anthony Celi.arXiv:2604.12152 (2026)… See the full description on the dataset page: https://huggingface.co/datasets/sebasmos/latent-sr-embeddings.srtm-global-void-filledThis dataset mirrors the
Shuttle Radar Topography Mission (SRTM) Void Filled digital elevation data from USGS.
It consists of the 15,417 GeoTIFFs available on USGS EarthExplorer in the "SRTM Void Filled" (srtm_v2) dataset.
Each GeoTIFF covers 1x1 degrees.
The data is in WGS84, with a resolution of 1 arc-second/pixel in the United States and 3 arc-seconds/pixel elsewhere.
Coverage is limited to "80% of the Earth's land surface between 60° north and 56° south latitude".
The data is attributed to… See the full description on the dataset page: https://huggingface.co/datasets/allenai/srtm-global-void-filled.
