Filtering this domain · category scientific-and-biomedical-data · 8 matching cards.
This repository is the collection of SLAM-related datasets. Among various SLAM datasets, we've selected the datasets provide pose and map information. This repository is linked to the google site. In this repository, the overall dataset chart is represented as simplified version. Use it to navigate the topic and choose relevant methods, papers or tools.
This is a collection of pointers to datasets/tasks/benchmarks pertaining to the intersection of machine learning and law. Use it to navigate the topic and choose relevant methods, papers or tools.
A curated list of awesome Bioinformatics software, resources, and libraries. Mostly command line based, and free or open-source. Please feel free to contribute!. Use it as a repeatable review, validation or hardening pass.
A curated reference on scientific & biomedical data centered on A 3D multi-modal medical image segmentation library in PyTorch. Use it to ground design choices in named patterns, trade-offs and examples.
This is a curated list of medical data for machine learning. This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here. Use it to ground design choices in named patterns, trade-offs and examples.
Segment Anything Model (SAM) uses vision transformer-based image encoder to extract image features and compute an image embedding, and prompt encoder to embed prompts and incorporate user interactions. Then extranted information from two encoders are combined to alightweight mask. Use it to navigate the topic and choose relevant methods, papers or tools.
Kaolin packages reusable building blocks from NVIDIA 3D research into a cohesive PyTorch API — continuously improving representation-agnostic physics simulation, fast conversions between representations, quaternion math, batched mesh and splat containers, I/O, visualization and m. Use it to build a structured path from fundamentals to hands-on practice.
Overview of medical image segmentation challenges in MICCAI 2023. Use it to navigate the topic and choose relevant methods, papers or tools.
Filtering this domain · category scientific-and-biomedical-data · 8 matching cards.
This repository is the collection of SLAM-related datasets. Among various SLAM datasets, we've selected the datasets provide pose and map information. This repository is linked to the google site. In this repository, the overall dataset chart is represented as simplified version. Use it to navigate the topic and choose relevant methods, papers or tools.
This is a collection of pointers to datasets/tasks/benchmarks pertaining to the intersection of machine learning and law. Use it to navigate the topic and choose relevant methods, papers or tools.
A curated list of awesome Bioinformatics software, resources, and libraries. Mostly command line based, and free or open-source. Please feel free to contribute!. Use it as a repeatable review, validation or hardening pass.
A curated reference on scientific & biomedical data centered on A 3D multi-modal medical image segmentation library in PyTorch. Use it to ground design choices in named patterns, trade-offs and examples.
This is a curated list of medical data for machine learning. This list is provided for informational purposes only, please make sure you respect any and all usage restrictions for any of the data listed here. Use it to ground design choices in named patterns, trade-offs and examples.
Segment Anything Model (SAM) uses vision transformer-based image encoder to extract image features and compute an image embedding, and prompt encoder to embed prompts and incorporate user interactions. Then extranted information from two encoders are combined to alightweight mask. Use it to navigate the topic and choose relevant methods, papers or tools.
Kaolin packages reusable building blocks from NVIDIA 3D research into a cohesive PyTorch API — continuously improving representation-agnostic physics simulation, fast conversions between representations, quaternion math, batched mesh and splat containers, I/O, visualization and m. Use it to build a structured path from fundamentals to hands-on practice.
Overview of medical image segmentation challenges in MICCAI 2023. Use it to navigate the topic and choose relevant methods, papers or tools.