42 citations · 47 across the 11 of their papers we have counts for
11 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…
Towards eXplainable AI for Mobility Data Science
Anahid Jalali, Anita Graser, Clemens Heistracher
This paper presents our ongoing work towards XAI for Mobility Data Science applications, focusing on explainable models that can learn from dense trajectory data, such as GPS track…
Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms
Lam Pham, Dat Ngo, Cam Le +2
In this technical report, a low-complexity deep learning system for acoustic scene classification (ASC) is presented. The proposed system comprises two main phases: (Phase I) Train…
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…
Low-complexity deep learning frameworks for acoustic scene classification
Lam Pham, Dat Ngo, Anahid Jalali +1
In this report, we presents low-complexity deep learning frameworks for acoustic scene classification (ASC). The proposed frameworks can be separated into four main steps: Front-en…
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…
Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios
Alexander Schindler, Andrew Lindley, Anahid Jalali +3
The forensic investigation of a terrorist attack poses a significant challenge to the investigative authorities, as often several thousand hours of video footage must be viewed. La…
Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning
Anahid Jalali, Clemens Heistracher, Alexander Schindler +5
Predicting unscheduled breakdowns of plasma etching equipment can reduce maintenance costs and production losses in the semiconductor industry. However, plasma etching is a complex…