Envelope: Shaping the Future of Computer Vision for Retail
Envelope develops cutting-edge computer vision to extract essential information from images, videos, and camera streams
Envelope develops cutting-edge computer vision to extract essential information from images, videos, and camera streams
Tracebloc builds a platform where enterprises can showcase challenges and source machine learning models to solve these.
Alpha AR uses machine learning to automate the entire process of creating 3D models of real-world objects.
The startup SpiNNcloud System is on a mission to build a cognitive computer, a ‘brain’ encoded by electronic integrated circuits.
deepset provides tools to develop natural language interfaces quickly and efficiently and created the open-source framework Haystack.
Neurolabs uses synthetic images to update computer vision models within hours instead of weeks e.g for supermarket checkouts.
The Latvian startup Enot develops an AutoML framework for neural network compression and acceleration for the edge.
NannyML detects silent model failures that happen post-deployment – estimating model performance before historical data is available.
Qdrant: Shaping the Future of Neural Search & Metric Learning Have you ever used Google’s image search? Instead of searching for keywords, you upload an actual image, and the algorithm finds similar images – based on a machine learning algorithm called vector similarity search. It is one example algorithm for neural search: using deep neural …
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