◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Romain Giot

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.DS1
  • cs.NE1
  • cs.OH1
ORCID 0000-0002-0638-7504

identity via Semantic Scholar / OpenAlex

most citedFast computation of the performance evaluation of biometric systems: application to multibiometric

41 citations · 85 across the 4 of their papers we have counts for

collaborators
Showing cs.CVShow all

3 papers · 1 filter

cs.CV2024

Mean Opinion Score as a New Metric for User-Evaluation of XAI Methods

Hyeon Yu, Jenny Benois-Pineau, Romain Bourqui +2

This paper investigates the use of Mean Opinion Score (MOS), a common image quality metric, as a user-centric evaluation metric for XAI post-hoc explainers. To measure the MOS, a u…

cs.CV2023

On the stability, correctness and plausibility of visual explanation methods based on feature importance

Romain Xu-Darme, Jenny Benois-Pineau, Romain Giot +4

In the field of Explainable AI, multiples evaluation metrics have been proposed in order to assess the quality of explanation methods w.r.t. a set of desired properties. In this wo…

cs.CV2023★ 7 cited

Evaluation of Explanation Methods of AI -- CNNs in Image Classification Tasks with Reference-based and No-reference Metrics

A. Zhukov, J. Benois-Pineau, R. Giot

The most popular methods in AI-machine learning paradigm are mainly black boxes. This is why explanation of AI decisions is of emergency. Although dedicated explanation tools have…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.