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Found 4 papers, 2 papers with code
Adaptive Confidence Multi-View Hashing for Multimedia Retrieval
Furthermore, an adaptive confidence multi-view network is employed to measure the confidence of each view and then fuse multi-view features through a weighted summation.
Central Similarity Multi-View Hashing for Multimedia Retrieval
Hash representation learning of multi-view heterogeneous data is the key to improving the accuracy of multimedia retrieval.
Deep Metric Multi-View Hashing for Multimedia Retrieval
However, existing methods fail to effectively fuse the multi-view features and utilize the metric information provided by the dissimilar samples, leading to limited retrieval precision.
AutoGMap: Learning to Map Large-scale Sparse Graphs on Memristive Crossbars
But the exploration of large-scale sparse graph computing on processing-in-memory (PIM) platforms (typically with memristive crossbars) is still in its infancy.
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