Publications
Invited Presentations
| Autor | Titel | Where | Year | Link |
|---|---|---|---|---|
| Axel Jantsch | DNN partitioning for IoT nodes | APROPOS Summer School | 2023 | pdf, opens an external URL in a new window |
| Axel Jantsch | Embedded machine learning | AVL Tech Trends | 2022 | pdf, opens an external URL in a new window |
| Axel Jantsch | Efficient inference at the edge | TECoSA Seminar at the Center for Trustworthy Edge Computing Systems and Applications | 2022 | pdf, opens an external URL in a new window |
| Axel Jantsch and Zhonghai Lu | Embedded machine learning | Summer School on Cyber-Physical Systems and Internet-of-Things | 2022 | pdf, opens an external URL in a new window |
| Axel Jantsch | Embedded machine learning | AVL Open Networking Day | 2021 | pdf, opens an external URL in a new window |
| Horst Bischof | Computer vision for detection and tracking | Summer School on AI Enabled Mobility | 2020 | |
| Axel Jantsch | Embedded machine learning | Summer School on AI Enabled Mobility | 2020 | pdf, opens an external URL in a new window |
Journal Articles
| Autor | Titel | Journal | Year | Link |
|---|---|---|---|---|
| Matthias Wess, Daniel Schnöll, Dominik Dallinger, Matthias Bittner, Axel Jantsch | Conformal Prediction Based Confidence for Latency Estimation of DNN Accelerators: A Black-Box Approach | IEEE Access | 2024 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Martin Lechner and Axel Jantsch | Blackthorn: Latency Estimation Framework for CNNs on Embedded Nvidia Platforms | IEEE Access | 2021 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Matthias Wess, M. Ivanov, C. Unger, A. Nookala, Alexander Wendt, and Axel Jantsch | Annette: Accurate neural network execution time estimation with stacked models | IEEE Access | 2021 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Amid Mozelli, Nima Taherinejad, and Axel Jantsch | A study on confidence: an unsupervised multi-agent machine learning experiment | IEEE Design & Test of Computers | 2021 | DOI, opens an external URL in a new window |
| Nima TaheriNejad, Andreas Herkersdorf, and Axel Jantsch | Autonomous systems, trust and guarantees | IEEE Design Test, pages 1–1 | 2020 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Henrik Hoffmann, Axel Jantsch, and Nikil D. Dutt | Embodied self-aware computing systems | IEEE, pages 1–20 | 2020 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Kerstin Bellman, Nikil Dutt, Lukas Esterle, Andreas Herkersdorf, Axel Jantsch, C. Landauer, P. R.Lewis, M. Platzner, N. TaheriNejad, and K. Tammemäe | Self-aware cyber-physical systems | ACM Transactions on Cyber-Physical Systems, 4(4):1–24 | 2020 | DOI, opens an external URL in a new window |
Conference Papers
| Autor | Titel | Conference | Year | Link |
|---|---|---|---|---|
| Sanaa Hobeichi, Yawen Shao, Rampal Neelesh, Matthias Bittner, Gab Abramowitz | Revisiting Tabular Machine Learning and Sequential Models to Advance Climate Downscaling | EGU24 General Assembly | 2024 | DOI, opens an external URL in a new window |
| Axel Jantsch, Song Han, Lin Meng, Oliver Bringmann, Haotian Tang, Shang Yang Hengyi Li, Matthias Wess, Martin Lechner | Special Session: Estimation and Optimization of DNNs for Embedded Platforms | ESWEEK CODES-ISSS | 2024 | DOI, opens an external URL in a new window pdf, opens an external URL in a new window |
| Daniel Schnöll, Dominik Dallinger, Matthias Wess, Matthias Bittner, and Axel Jantsch | Towards Optimal Implementations of Neural Networks on Micro-Controller | ITEM: IoT, Edge, and Mobile for Embedded Machine Learning at ECML PKDD | 2024 | |
| Matthias Bittner, Daniel Hauer, Matthias Wess, Daniel Schnöll, Konrad Diwold, Axel Jantsch | Forecasting Critical Load Profiles with Uncertainty Quantification for Low Voltage Heterogeneous Smart Grids | International Conference on System Reliability and Safety | 2024 | |
| Matthias Bittner, Daniel Hauer, Matthias Wess, Dominik Dallinger, Daniel Schnöll, Konrad Diwold, Axel Jantsch | Interpretable Load Forecasting with Structured State Space Neural Networks | Machine Learning for Sustainable Power Systems Workshop at ECML PKDD | 2024 | |
| David Breuss, Karel Rusý, Maximilian Götzinger, Axel Jantsch | Generation of Synthetic Image Anomalies for Analysis | International Conference on Intelligent Systems and Patterns Recognition | 2024 | |
| Georg Krispel, David Schinagl, Christian Fruhwirth-Reisinger, Horst Possegger, Horst Bischof | MAELi: Masked Autoencoder for Large-Scale LiDAR Point Clouds | Winter Conference on Applications of Computer Vision (WACV) | 2024 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Leonid Karlinsky, Wei Lin, Sivan Doveh, Jakub Micorek, Mateusz Kozinski, Hilde Kuehne, Horst Possegger | Meta-Prompting for Automating Zero-shot Visual Recognition with LLMs | European Conference on Computer Vision | 2024 | pdf, opens an external URL in a new window |
| Christian Fruhwirth-Reisinger, Wei Lin, Dusan Malić, Horst Bischof, Hosrt Possegger | Vision-Language Guidance for LiDAR-based Unsupervised 3D Object Detection | British Machine Vision Conference (BMVC) | 2024 | pdf, opens an external URL in a new window |
| Matthias Bittner, Andreas Hinterreiter, Klaus Eckelt, Marc Streit | Explainable Long- and Short-term Pattern Detection in Projected Sequential Data | ECML PKDD Workshop on Explainable AI for Time Series: Advances and Applications | 2023 | DOI, opens an external URL in a new window |
| Matthias Bittner, Sanaa Hobeichi, Muhammad Zawish, Samo Diatta, Remigious Ozioko, Sharon Xu, Axel Jantsch | An LSTM-based downscaling framework for australian precipitation projections | NeurIPS 2023 Workshop: Tackling Climate Change with Machine Learning at the Conference on Neural Information Processing Systems | 2023 | pdf, opens an external URL in a new window |
| Matthias Bittner, Daniel Hauer, Christian Stippel, Katharina Scheucher, Robin Sudhoff, Axel Jantsch | Forecasting critical overloads based on heterogeneous smart grid simulation | International Conference on Machine Learning and Applications (IEEE and AMLA) | 2023 | pdf, opens an external URL in a new window |
| David Breuss, Maximilian Götzinger, Jenny Vuong, Clemens Reisner, and Axel Jantsch | VADAR: A Vision-based Anomaly Detection Algorithm for Railroads | 26th Euromicro Conference on Digital System Design (DSD) | 2023 | pdf, opens an external URL in a new window |
| Christian Fruhwirth-Reisinger, Wei Lin, Dusan Malic, David Schinagl, Georg Krispel, Horst Possegger, Horst Bischof | Unsupervised Class-aware 3D Object Detection in LiDAR Point Clouds | Conference on Neural Information Processing Systems (NeurIPS) | 2023 | |
| Stefan Leitner, M Jehanzeb Mirza, Wei Lin, Jakub Micorek, Marc Masana, Mateusz Kozinski, Horst Possegger, Horst Bischof | Sit Back and Relax: Learning to Drive Incrementally in All Weather Conditions | IEEE Intelligent Vehicle Symposium (IV) | 2023 | pdf, opens an external URL in a new window |
| David Schinagl, Georg Krispel, Christian Fruhwirth-Reisinger, Horst Possegger, Horst Bischof | GACE: Geometry Aware Confidence Enhancement for Black-box 3D Object Detectors on LiDAR-Data | International Conference on Computer Vision (ICCV) | 2023 | pdf, opens an external URL in a new window |
| Martin Lechner, Axel Jantsch | OptiSim: A Hardware-Aware Optimization Space Exploration Tool for CNN Architectures | ITEM Workshop at ECML PKDD | 2023 | |
| Daniel Schnöll, Matthias Wess, Matthias Bittner, Maximilian Götzinger, Axel Jantsch | Fast, Quantization Aware DNN Training for Efficient HW Implementation | DSD Conference | 2023 | pdf, opens an external URL in a new window |
| Matthias Wess, Dominik Dallinger, Daniel Schnöll, Matthias Bittner, Maximilian Götzinger, Axel Jantsch | Energy Profiling of DNN Accelerators | DSD Conference | 2023 | pdf, opens an external URL in a new window |
| Thomas Kotrba, Martin Lechner, Omair Sarwar and Axel Jantsch | Multispectral Feature Fusion for Deep Object Detection on Embedded NVIDIA Platforms | DATE Conference | 2023 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Inkyu Shin, Wei Lin, Andreas Schriebl, Kunyang Sun, Jaesung Choe, Horst Possegger, Mateusz Kozinski, In So Kweon, Kun-Jin Yoon, Horst Bischof | MATE: Masked Autoencoders are Online 3D Test-Time Learners | International Conference on Computer Vision (ICCV) | 2023 | pdf, opens an external URL in a new window |
| Wei Lin, Muhammad Jehanzeb Mirza, Mateusz Kozinski, Horst Possegger, Hilde Kuehne, Horst Bischof | Video Test-Time Adaptation for Action Recognition | Conference on Computer Vision and Pattern Recognition (CVPR) | 2023 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Pol Jané Soneira, Wei Lin, Mateusz Kozinski, Horst Possegger, Horst Bischof | ActMAD: Activation Matching to Align Distributions for Test-Time-Training | Conference on Computer Vision and Pattern Recognition (CVPR) | 2023 | pdf, opens an external URL in a new window |
| Dusan Malić, Christian Fruhwirth-Reisinger, Horst Possegger, Horst Bischof | SAILOR: Scaling Anchors via Insights into Latent Object Representation | Winter Conference on Applications of Computer Vision (WACV) | 2023 | pdf, opens an external URL in a new window |
| Martin Lechner, Lukas Steindl, Axel Jantsch | Study of DNN-based Ragweed Detection from Drones | SAMOS Conference | 2022 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Marc Masana, Horst Possegger, Horst Bischof | An Efficient Domain-Incremental Learning Approach to Drive in All Weather Conditions | Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | 2022 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Jakub Micorek, Horst Possegger, Horst Bischof | The Norm Must Go On: Dynamic Unsupervised Domain Adaptation by Normalization | Conference on Computer Vision and Pattern Recognition (CVPR) | 2022 | pdf, opens an external URL in a new window |
| David Schinagl, Georg Krispel, Peter Roth, Horst Possegger, Horst Bischof | OccAM’s Laser: Occlusion-based Attribution Maps for 3D Object Detectors on LiDAR Data | Conference on Computer Vision and Pattern Recognition (CVPR) | 2022 | pdf, opens an external URL in a new window |
| Christian Fruhwirth-Reisinger, Michael Opitz, Horst Possegger and Horst Bischof | FAST3D: Flow-Aware Self-Training for 3D Object Detectors | British Machine Vision Conference (BMVC) | 2021 | pdf, opens an external URL in a new window |
| A. Glinserer, M. Lechner and A. Wendt | Automated Pruning of Neural Networks for Mobile Applications | IEEE 19th International Conference on Industrial Informatics (INDIN), pp. 1-6 | 2021 | pdf, opens an external URL in a new window |
| Muhammad Jehanzeb Mirza, Cornelius Buerkle, Julio Jarquin, Michael Opitz, Fabian Oboril, Kay-Ulrich Scholl, and Horst Bischof | Robustness of Object Detectors in Degrading Weather Conditions | International Conference on Intelligent Transportation Systems (ITSC) | 2021 | pdf, opens an external URL in a new window |
| Bernhard Haas, Alexander Wendt, Axel Jantsch, and Matthias Wess | Neural network compression through shunt connections and knowledge distillation for semantic segmentation problems | AIAI 2021, 17th International Conference on Artificial Intelligence Applications and Innovations, volume 1 | 2021 | DOI, opens an external URL in a new window |
| Georg Krispel, Michael Opitz, Georg Waltner, Horst Possegger, and Horst Bischof | Fuseseg: Lidar point cloud segmentation fusing multi-modal data | Winter Conference on Applications of Computer Vision (WACV) | 2020 | pdf, opens an external URL in a new window |
| Stefan Holly, Alexander Wendt, and Martin Lechner | Profiling energy consumption of deep neural networks on nvidia jetson nano | 11th International Green and Sustainable ComputingWorkshops (IGSC), pages 1–6 | 2020 | DOI, opens an external URL in a new window |
| Alexander Wendt, Marco Wuschnig, and Martin Lechner | Speeding up common hyperparameter optimization methods by a two-phase-search | IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, pages 517–522 | 2020 | http, opens an external URL in a new window |
| Alexander Wendt, Stefan Kollmann, Aleksey Bratukhin, Alireza Estaji, Thilo Sauter, and Axel Jantsch | Cognitive architectures for process monitoring - an analysis | 18thIEEE International Conference on Industrial Informatics, pages 167–173 | 2020 | pdf, opens an external URL in a new window |
| Christian Fruhwirth-Reisinger, Georg Krispel, Horst Possegger, and Horst Bischof | Towards data-driven multi-target tracking for autonomous driving | Computer Vision Winter Workshop (CVWW) | 2020 | pdf, opens an external URL in a new window |
Bachelor- and Mastertheses
| Author | Title | Type | Year | Link |
|---|---|---|---|---|
| Stefan Schüttengruber | Noise Filtering using Structured State Space Neural Networks targeting MCUs | Bachelorarbeit | 2024 | |
| Stefan Dangl | BPLS back propagation layer scheduling | Masterarbeit | 2024 | reposiTUm, opens an external URL in a new window |
| Matthias Dippold | Benchmarking Deep Learning Inference Frameworks on Cortex-M4 Microcontrollers | Bachelorarbeit | 2024 | |
| Christina Thrainer | Lidar-based 3d object detection with rgb point painting | Bachelorarbeit | 2023 | |
| Markus Ostojic | Enhancing 3d object detection via deformable convolution | Bachelorarbeit | 2023 | |
| Darjan Babic | Evaluating normalizing flows | Bachelorarbeit | 2023 | |
| Bernhard Ruhm | RNN-based Time Series Classification on MCUs | Bachelorarbeit | 2023 | |
| Thomas Kotrba | Simultanous multispectral detection of objects | Mastertheses | 2023 | reposiTUm, opens an external URL in a new window |
| Alex Ludwig | Optimizing of siamese object tracking networks | Mastertheses | 2023 | reposiTUm, opens an external URL in a new window |
| Lukas Steindl | Optimizing deep neural networks for efficient dronebased ragweed detection | Mastertheses | 2022 | reposiTUm, opens an external URL in a new window |
| Nicolas Alge | Power Profiling of Machine Learning Accelerators using MLPerf | Bachelortheses | 2022 | http, opens an external URL in a new window |
| David Radu Andrei | Real time simultaneous face detection and pose estimation | Bachelortheses | 2022 | |
| Julian Westra | Optimization of a deep neural network on intel OpenVino for a pedestrian detection algorithm | Bachelortheses | 2022 | |
| Alon Tchelet | Embedded High Speed Object Detection with Quantized Neural Networks | Mastertheses | 2022 | |
| Fabian Scherer | FPGA evaluation of YOLO object detection. | Bachelortheses | 2021 | |
| Michael Optiz (TU Graz) | Efficient Ensembles for Deep Learning | PhD | 2021 | pdf, opens an external URL in a new window |
| Amid Mozelli | A Study on Confidence: an Unsupervised Multi-Agent Machine Learning Experiment | Bachelortheses | 2021 | |
| Andreas Glinserer | Autopruning with intel distiller and evaluation on a Jetson Xavier AGX | Mastertheses | 2021 | reposiTUm, opens an external URL in a new window |
| Bernhard Haas | Compressing MobileNet with shunt connections for NVIDIA hardware | Mastertheses | 2021 | reposiTUm, opens an external URL in a new window |
| Lukas Baischer | FPGA Based Embedded Neural Network Object Detector | Mastertheses | 2021 | reposiTUm, opens an external URL in a new window |
| Dominik Dallinger | FPGA optimized dynamic post-training quantization of TinyYoloV3 | Bachelortheses | 2021 | pdf, opens an external URL in a new window |
| Matvey Ivanov | Embedded Machine Learning Demonstrator | Bachelortheses | 2021 | pdf, opens an external URL in a new window |
| Marco Leber-Wuschnig | Auswertung verschiedener Methoden der Hyperparameteroptimierung in Machine Learning | Bachelortheses | 2020 | pdf, opens an external URL in a new window |
| Alemajehu Kaleab Kinfu (TU Graz) | Lifelong Learning for Autonomous Vehicles: Monocular Depth Estimation | Mastertheses | 2020 | |
| Anam Zahra (TU Graz) | Autonomous Vehicle Self-localization in Noisy Environments | Mastertheses | 2020 |
Contact
Christian Doppler Laboratory for Embedded Machine Learning
TU Wien
Institute of Computer Technology
Gusshausstrasse 27-29, 1040 Vienna, Austria
Phone: +43 1 58801 38401
Email: cdleml@tuwien.ac.at
Visit us
About us, opens an external URL in a new window
GitHub Repositories, opens an external URL in a new window
Scripts and Guides by CDL EML, opens an external URL in a new window
Institut of Computertechnik TU Wien, opens an external URL in a new window
Institute of Computer Graphics and Vision TU Graz, opens an external URL in a new window
Contact
Christian Doppler Laboratory for Embedded Machine Learning
TU Wien
Institute of Computer Technology
Gusshausstrasse 27-29, 1040 Vienna, Austria
Phone: +43 1 58801 38401
Email: cdleml@tuwien.ac.at
Visit us
About us, opens an external URL in a new window
GitHub Repositories, opens an external URL in a new window
Scripts and Guides by CDL EML, opens an external URL in a new window
Institut of Computertechnik TU Wien, opens an external URL in a new window
Institute of Computer Graphics and Vision TU Graz, opens an external URL in a new window