A Proposal for the Management of the Measurement Uncertainty in Classification and Recognition Problems

Giovanni Betta · Domenico Capriglione · Mariella Corvino · Consolatina Liguori · Alfredo Paolillo

10 citations0/0 files storedIEEE Transactions on Instrumentation and Measurement

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Scientific Measurement and Uncertainty Evaluation Face recognition and analysis Face and Expression Recognition

Abstract

This paper proposes a new approach to classification and recognition problems. It considers the measurement uncertainty affecting input data to improve the overall effectiveness of this type of process. The proposed method is based on an effective probabilistic approach for the evaluation of the confidence level of system outputs and the suitable use of related information to improve the performance in terms of the correct decision rate. As a case study, it is applied to a particular face recognition classification algorithm based on linear discrimination analysis. The performance comparison with a traditional approach has proven the value of the proposal.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 10 citations exist upstream.

References

2011On the fusion of imprecise uncertainty measures using belief structures

Imported from OpenAlex (CC0) — nothing here is generated.