Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study
Summary
Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study is a scholarly article[1].
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Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study's instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study. Retrieved May 24, 2026, from https://4ort.xyz/entity/improving-explainable-ai-with-patch-perturbation-based-evaluation-pipeline-a-covid-19-x-ray-image-analysis-case-study
MLA“Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/improving-explainable-ai-with-patch-perturbation-based-evaluation-pipeline-a-covid-19-x-ray-image-analysis-case-study.
BibTeX@misc{4ortxyz_improving-explainable-ai-with-patch-perturbation-based-evaluation-pipeline-a-covid-19-x-ray-image-analysis-case-study_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study}}, year = {2026}, url = {https://4ort.xyz/entity/improving-explainable-ai-with-patch-perturbation-based-evaluation-pipeline-a-covid-19-x-ray-image-analysis-case-study}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study — https://4ort.xyz/entity/improving-explainable-ai-with-patch-perturbation-based-evaluation-pipeline-a-covid-19-x-ray-image-analysis-case-study (retrieved 2026-05-24)
