Open Access
Interactive Machine Learning tool with Automatic Tagging for Video Recognition System
Fujio Tsutsumi,Iwado Kita +1 more
- 01 Jan 2006
TL;DR: A new approach to solve the feedback delay and low visibility problem of conventional IML handling large-scale data is proposed, which features high-speed feedback using an approximate nearest neighbor, process controllability by the user, and priority based visualization.
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Abstract: Interactive machine learning (IML) is proposedto train intelligent systems. This paper proposes a new approach to solve the feedback delay and low visibility problem of conventional IML handling large-scale data. The approach features high-speed feedback using an approximate nearest neighbor, process controllability by the user, and priority based visualization. The validity of the approach is shown by an experiment with a prototype using a video where the lighting changes.
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References
Locality-sensitive hashing scheme based on p-stable distributions
Mayur Datar,Nicole Immorlica,Piotr Indyk,Vahab Mirrokni +3 more
- 08 Jun 2004
TL;DR: A novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under lp norm, based on p-stable distributions that improves the running time of the earlier algorithm and yields the first known provably efficient approximate NN algorithm for the case p<1.
Interactive machine learning
Jerry Alan Fails,Dan R. Olsen +1 more
- 12 Jan 2003
TL;DR: An interactive machine-learning (IML) model that allows users to train, classify/view and correct the classifications and the Crayons tool embodies the notions of interactive machine learning is proposed.
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