2 citations · 3 across the 7 of their papers we have counts for
8 papers
MobilityDL: A Review of Deep Learning From Trajectory Data
Anita Graser, Anahid Jalali, Jasmin Lampert +2
Trajectory data combines the complexities of time series, spatial data, and (sometimes irrational) movement behavior. As data availability and computing power have increased, so ha…
Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis
Anahid Jalali, Bernhard Haslhofer, Simone Kriglstein +1
Post-hoc explainability methods aim to clarify predictions of black-box machine learning models. However, it is still largely unclear how well users comprehend the provided explana…
Robust, General, and Low Complexity Acoustic Scene Classification Systems and An Effective Visualization for Presenting a Sound Scene Context
Lam Pham, Dusan Salovic, Anahid Jalali +4
In this paper, we present a comprehensive analysis of Acoustic Scene Classification (ASC), the task of identifying the scene of an audio recording from its acoustic signature. In p…
Machine Learning Methods for Health-Index Prediction in Coating Chambers
Clemens Heistracher, Anahid Jalali, Jürgen Schneeweiss +3
Coating chambers create thin layers that improve the mechanical and optical surface properties in jewelry production using physical vapor deposition. In such a process, evaporated…
Minimal-Configuration Anomaly Detection for IIoT Sensors
Clemens Heistracher, Anahid Jalali, Axel Suendermann +4
The increasing deployment of low-cost IoT sensor platforms in industry boosts the demand for anomaly detection solutions that fulfill two key requirements: minimal configuration ef…
A Low-Compexity Deep Learning Framework For Acoustic Scene Classification
Lam Pham, Hieu Tang, Anahid Jalali +2
In this paper, we presents a low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed framework can be separated into three main steps: Front-e…