Capturing significant events with neural networks.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 22402410.
- Also identified by DOI 10.1016/j.neunet.2012.01.003.
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Abstract
Smartphone video capture and transmission to the Web contributes to data pollution. In contrast, mammalian eyes sense all, capture only significant events, allowing us vividly recall the causalities. Likewise in our videos, we wish to skip redundancies and keep only significantly differences, as determined by real-time local medium filters. We construct a Picture Index (PI) of one's (center of gravity changes) among zeros (no changes) as Motion Organized Sparseness (MOS). Only non-overlapping time-ordered PI pair is admitted in the outer-product Associative Memory (AM). Another outer product between PI and its image builds Hetero-AM (HAM) for fault tolerant retrievals.
Medical subject headings
- Association Learning
- Cell Phone
- Neural Networks, Computer
- Pattern Recognition, Visual
- Photic Stimulation