IJFANS International Journal of Food and Nutritional Sciences

Volume 13 Issue 4

Effect of Biostimulants (Azospirillum, Pseudomonas and Bacillus) on the growth and disease suppression of neem Azadirachta indica (A) juss.seedlings
Volume 13 | Issue 4

“Pigments of Imagination & Color Psychology of Consumers towards Apparel: A Perceptual Study”
Volume 13 | Issue 4

Exploring The Relationship Between Weather Patterns and Energy Consumption in Smart Homes: A Regression Analysis
Volume 13 | Issue 4

DEEP LEARNING BASED APPROACH FOR BIRD SPECIES IDENTIFICATION AND CLASSIFICATION
Volume 13 | Issue 4

ML-DRIVEN WASTE CLASSIFICATION FOR EFFECTIVE ORGANIC AND NON-ORGANIC WASTE MANAGEMENT
Volume 13 | Issue 4

Explainable Artificial Intelligence (XAI)

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Keywords:

Explainable AI, XAI, Interpretability, Machine Learning Transparency, Decision-making Accountability, Ethical AI, LIME, SHAP, Model-agnostic Explanations, Interpretable Models, Performance vs. Interpretability, User Trust in AI, Real-world Applications of XAI, Regulatory Landscape in AI Explain-ability

Sangeeta Sharma, Karan Kaushik, Rachita Sharma, Nikita Chaturvedi
» doi: 10.48047/ijfans/v12/i1/271

Abstract

Explainable Artificial Intelligence (XAI) has emerged as a critical facet in the realm of machine learning and artificial intelligence, responding to the increasing complexity of models, particularly deep neural networks, and the subsequent need for transparent decisionmaking processes.

Issue

Volume 12, Issue 1 (2023 )

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