Results 201 to 210 of about 85,609 (269)
Applied AI Letters, Volume 7, Issue 2, June 2026.In this work, we have performed human‐based evaluation of three post hoc explainability techniques, Local Interpretable Model Agnostic Explanations (LIME), Shapely Additive Explanations (SHAP), and integrated Gradients (IG) for a multilingual Bidirectional Encoder Representations from Transformers (mBERT) based binary and multi‐label misogyny ...
Sargam Yadav +2 more
wiley +1 more source
A multi-layered defense against adversarial attacks in brain tumor classification using ensemble adversarial training and feature squeezing. [PDF]
Sci RepYinusa A, Faezipour M.
europepmc +1 more source
Cross‐Method Explanation Stability Under Prediction‐Preserving Perturbations in Explainable AI
Applied AI Letters, Volume 7, Issue 2, June 2026.The cross‐method analysis showed common vulnerability patterns across gradient‐based and perturbation‐based explainers, whereas Grad‐CAM demonstrated a specific ability to be resilient. Further discussion revealed that, before prediction changes with increasing ε, explanation divergence could already have commenced, indicating that further explanation ...
Muhammad Hasnain +4 more
wiley +1 more source
Channel Attention for Fire and Smoke Detection: Impact of Augmentation, Color Spaces, and Adversarial Attacks. [PDF]
Sensors (Basel)Ejaz U, Hamza MA, Kim HC.
europepmc +1 more source
eFood, Volume 7, Issue 3, June 2026.This review synthesizes AI advancements in food systems, leveraging machine learning, computer vision, robotics, and IoT for 96%–100% accurate quality inspection, 30% reduced downtime, and enhanced traceability from farm to fork. It highlights transformative potential in sustainability and SDGs while addressing data, ethical, and scalability challenges
Muhammad Waqar +9 more
wiley +1 more source
Salient object detection dataset with adversarial attacks for genetic programming and neural networks. [PDF]
Data BriefOlague M +3 more
europepmc +1 more source
eFood, Volume 7, Issue 3, June 2026.AI application can be very helpful in addressing different issues and shaping novel techniques in food production, food safety and quality, and food intake. AI application in food science, such as the food industry and processing, food safety and packaging, and nutrition.
Yaseen Galali +7 more
wiley +1 more source
Auto encoder-based defense mechanism against popular adversarial attacks in deep learning. [PDF]
PLoS OneAshraf SN, Siddiqi R, Farooq H.
europepmc +1 more source
Improving Implied Volatility Forecasts for American Options Using Neural Networks
Journal of Futures Markets, Volume 46, Issue 6, Page 1137-1153, June 2026.ABSTRACT This paper explores the application of neural networks to improve pricing of American options. Focusing on both American and European options on the S&P 100 index from January 2016 to August 2023, we integrate neural networks to model the difference between market‐implied and model‐implied volatilities derived from the Black‐Scholes and Heston
Haitong Jiang, Emese Lazar, Miriam Marra
wiley +1 more source
Recommender Systems: Taxonomy, Applications and Current Research Trends
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.Integrating taxonomy, application developments, open‐source software, and publication trends, this paper identifies and outlines promising future directions for recommender systems research. ABSTRACT Recommender Systems play an essential role in assisting users to navigate the immense amount of information and services available online, aiding them in ...
Daniel Ranchal‐Parrado +2 more
wiley +1 more source