Learning to Hash with Binary Reconstructive Embeddings
Impact in
Classified as
- Authors
- Brian KulisTrevor Darrell
- Journal
- UC Berkeley
In The Last Decade
doi.org/w8481127 →Countries where authors are citing Learning to Hash with Binary Reconstructive Embeddings
This map shows the geographic impact of Learning to Hash with Binary Reconstructive Embeddings. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Learning to Hash with Binary Reconstructive Embeddings with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Learning to Hash with Binary Reconstructive Embeddings more than expected).
Fields of papers citing Learning to Hash with Binary Reconstructive Embeddings
This network shows the impact of Learning to Hash with Binary Reconstructive Embeddings. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Learning to Hash with Binary Reconstructive Embeddings.
About Learning to Hash with Binary Reconstructive Embeddings
This paper, published in 2009, received 534 indexed citations . Written by Brian Kulis and Trevor Darrell covering the research area of Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Computer Vision and Pattern Recognition (518 citations), Artificial Intelligence (89 citations), Aerospace Engineering (48 citations), Computer Networks and Communications (30 citations) and Signal Processing (24 citations). Published in UC Berkeley.
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This paper is also available at doi.org/w8481127.