Anahid Naghibzadeh-Jalali

Search results

• 2024

  MobilityDL: A Review of Deep Learning From Trajectory Data

  Graser, A., Naghibzadeh-Jalali, A., Lampert, J., Weißenfeld, A. & Janowicz, K., 28 May 2024, In: GeoInformatica. 28, 33 p.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Trajectory Data 100%
  • Deep Learning 100%
  • Use Case 25%
  • Deep Learning Model 25%
  • Tracking Data 25%
• 2023

  Decoding the Unknown: Unveiling Industrial Time Series Classification with Counterfactuals

  Naghibzadeh-Jalali, A., Rauber, A. & Lampert, J., 23 Jun 2023, In: ERCIM News - Special Thema: Explainable AI. 134, p. 28-29 2 p., 13.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Series Prediction 100%
  • Use Case 50%
  • Industrial Application 50%
  • Decision Trees 50%
  • Data Availability 50%

• Deep Learning from Trajectory Data: a Review of Deep Neural Networks and the Trajectory Data Representations to Train Them

  Graser, A. (Speaker), Naghibzadeh-Jalali, A., Lampert, J., Weißenfeld, A. & Janowicz, K., 2023, CEUR Workshop Proceedings 2023. Fletcher, G. & Kantere, V. (eds.). Vol. 3379. 12 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

  • Trajectory Data 100%
  • Deep Neural Network 100%
  • Deep Learning 100%
  • Data Representation 100%
  • Neural Network 100%

• Light-Weight Deep Learning Models for Acoustic Scene Classification Using Teacher-Student Scheme and Multiple Spectrograms

  Pham, L. (Speaker), Nguyen, T., Lam, P., Ngo, D., Naghibzadeh-Jalali, A. & Schindler, A., 2023, International Symposium on the Internet of Sounds . p. 1-8

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

  • Network Architecture 100%
  • Light-Weight Deep Learning Model 100%
  • Deep Learning 100%
  • Spectrogram 100%
  • Metro 66%

• Lightweight deep neural networks for acoustic scene classification and an effective visualization for presenting sound scene contexts

  Pham, L., Salovic, D., Naghibzadeh-Jalali, A., Schindler, A., Tran, K., Ngo, D., Nguyen, P. & Vu, C., Aug 2023, In: Applied Acoustics. 211, p. 1-18 18 p., 109489.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  • Deep Neural Network 100%
  • visualization method 100%
  • Model Complexity 66%
  • Classification Models 66%
  • Model Accuracy 33%

• Low-complexity deep learning frameworks for acoustic scene classification using teacher-student scheme and multiple spectrograms

  Pham, L., Ngo, D., Le, C., Naghibzadeh-Jalali, A. & Schindler, A., 2023, 3 p.

  Research output: Other contribution

  Open Access

  • Deep Learning 100%
  • Spectrogram 100%
  • Technical Report 50%

• Predictability and Comprehensibility in Post-Hoc XAI Methods: A User-Centered Analysis

  Naghibzadeh-Jalali, A. (Author and Speaker), Bernhard, H., Kriglstein, S. & Rauber, A., Sept 2023, Intelligent Computing. SAI 2023: Proceedings of the 2023 Computing Conference, Volume 1. Arai, K. (ed.). p. 712-733 (Lecture Notes in Networks and Systems (LNNS); vol. 711).

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

  • Misclassification 100%
  • Machine Learning 100%
  • Black Box 50%
  • Decision Boundary 50%
• 2022

  AI4 Trees – AI for climate sensitive tree growth modelling

  Zolles, A., Schüler, S., Lampert, J., Duro, R., Bronner, G., Kirchmeir, H., Naghibzadeh-Jalali, A. & Andreas, W., 10 Nov 2022. 1 p.

  Research output: Poster presentation without proceedings › peer-review

  Open Access

  File

  • Climate Change 100%
  • Growth Modeling 100%
  • Planetary Atmosphere 100%
  • Carbon Sequestration 100%
  • Forest Conservation 100%
  62 Downloads (Pure)

• AI for Climate Sensitive Tree Growth Modelling and Maximum Carbon Segregation (AI4Trees)

  Lampert, J. (Speaker), Duro, R. (Speaker), Bronner, G. (Speaker), Berger, V. (Speaker), Kirchmeir, H. (Speaker), Gritsch, M. (Speaker), Hewitt, D. (Speaker), Naghibzadeh-Jalali, A. (Speaker), Zolles, A. (Speaker) & Andreas, W. (Speaker), 30 Aug 2022.

  Research output: Poster presentation without proceedings › peer-review

• Ethical AI: Why and How

  Biegelbauer, P., Naghibzadeh-Jalali, A., Schlarb, S. & Vignoli, M., 2022, In: ERCIM News. 131, 131, p. 8-9 2 p.

  Research output: Contribution to journal › Article › peer-review
• 2021

  A Low-Complexity Deep Learning Framework For Acoustic Scene Classification

  Pham, L. (Speaker, Invited), Tang, H. (Author, Invited), Naghibzadeh-Jalali, A. (Author, Invited), Schindler, A. (Author, Invited) & King, R. C. (Author, Invited), 2021, Proceedings of the 4th International Data Science Conference – iDSC2021. Haber, P., Lampoltshammer, T., Leopold, H. & Mayr, M. (eds.). Springer, p. 45-50 6 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

  Open Access

• Transfer learning strategies for anomaly detection in iot vibration data

  Heistracher, C. (Speaker), Naghibzadeh-Jalali, A., Strobl, I., Suendermann, A., Meixner, S., Holly, S., Schall, D., Haslhofer, B. & Kemnitz, J., 2021, IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society. p. 1-6 6 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

  Open Access
• 2020

  Comparison of PSG signals and Respiratory Movement Signal via 3D Camera in Detecting Sleep Respiratory Events by LSTM Models

  Coronel, C. (Speaker), Wiesmeyr, C., Garn, H., Kohn, B., Naghibzadeh-Jalali, A., Schindler, A., Wimmer, M., Mandl, M., Glos, M., Penzel, T., Klösch, G., Stefanic-Kejik, A., Böck, M., Kaniusas, E. & Seidel, S., 2020, 2020 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

• Machine Learning Interpretability Techniques for Outage Prediction: A Comparative Study

  Naghibzadeh-Jalali, A. (Speaker, Invited), Schindler, A. (Author, Invited), Haslhofer, B. (Author, Invited) & Rauber, A. (Author, Invited), 2020, PHM papers PROCEEDINGS 2020. p. 1-10 10 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

• Multi-Modal Video Forensic Platform for Investigating Post-Terrorist Attack Scenarios

  Schindler, A. (Speaker), Lindley, A., Naghibzadeh-Jalali, A., Boyer, M., Gordea, S. & King, R. C., 2020, Proceedings of the 11th ACM Multimedia Systems Conference (MMSys2020). 3 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review
• 2019

  Predicting Time-to-Failure of Plasma Etching Equipment using Machine Learning

  Naghibzadeh-Jalali, A. (Author, Invited), Heistracher, C. (Speaker, Invited), Schindler, A. (Author, Invited), Haslhofer, B. (Author, Invited), Nemeth, T. (Author, Invited), Glawar, R. (Author, Invited), Sihn, W. (Author, Invited) & De Boer, P. (Author, Invited), 2019, 2019 IEEE International Conference on Prognostics and Health Management (ICPHM). p. 1-8 8 p.

  Research output: Chapter in Book or Conference Proceedings › Conference Proceedings with Oral Presentation › peer-review

• Understandable Deep Neural networks for Predictive Maintenance in the Manufactoring Industry

  Naghibzadeh-Jalali, A., Haslhofer, B. & Schindler, A., 2019, In: ERCIM News 116. 116, 1 p.

  Research output: Contribution to journal › Article
• 2018

  Sound Event detection with deep Neural Networks

  Naghibzadeh-Jalali, A., 2018

  Research output: Thesis › Master's Thesis