A dictionary learning paper whose abstract claims sparsity does not hurt recovery quality, but whose full text is an unrelated medical retrieval manuscript.
In: International Conference on Medi- cal Image Computing and Computer-Assisted Intervention
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Quality Versus Sparsity in Image Recovery by Dictionary Learning Using Iterative Shrinkage
A dictionary learning paper whose abstract claims sparsity does not hurt recovery quality, but whose full text is an unrelated medical retrieval manuscript.