A cloud-native vector database, storage for next generation AI applications
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Updated
May 19, 2024 - Go
A cloud-native vector database, storage for next generation AI applications
cuVS - a library for vector search and clustering on the GPU
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
Shotit is a screenshot-to-video search engine tailored for TV & Film, blazing-fast and compute-efficient.
Fast and minimal header-only graph-based index for approximate nearest neighbor search (ANNS).
EEG inverse solution with artificial neural networks. This package works with MNE-Python data structures for easy integration into your MNE-based M/EEG code
The frontend of shotit, with full documentation.
AI@UCF's custom-made course, organized by semesters
Data Mining Course @ The Open University
The ultimate brain of Shotit, in charge of task coordination.
Media broker for serving video preview for shotit
Four core workers of shotit: watcher, hasher, loader and searcher.
The README profile of Shotit.
Sort the search results of Shotit to increase the correctness of Top1 result by using Keras and Faiss.
Add a description, image, and links to the anns topic page so that developers can more easily learn about it.
To associate your repository with the anns topic, visit your repo's landing page and select "manage topics."