Publications by Axel Jantsch

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2024

[1] Florian Egert, Sofia Maragkou, Markus Kobelrausch, Bernhard Fischer, and Axel Jantsch. A Methodology for Automating the Integration of User-Defined Instructions into RISC-V Systems based on the CV-X-IF Interface. In RISC-V Summit Europe, Munich, Germany, June 2024. [ bib | .pdf ]
[2] Alireza Estaji, Maximilian Götzinger, Benedikt Tutzer, Stefan Kollmann, Thilo Sauter, and Axel Jantsch. Evaluation of Drift Detection Algorithms in the Condition Monitoring Domain. IEEE Transactions on Industrial Informatics, pages 1--10, 2024. [ bib | DOI | .pdf ]
[3] Thomas Leopold and Axel Jantsch. Colorado Potato Beetle Dataset and Detection for Monitoring and Management in Potato Fields. In Proceedings of the Austrian Symposion on AI, Robotics and Vision, Austria, 2024. [ bib | .pdf ]
[4] Muhammad Noman Sohail, Adeel Anjum, Iftikhar Ahmed Saeed, Madiha Haider Syed, Axel Jantsch, and Semeen Rehman. Optimizing Industrial IoT Data Security through Blockchain-Enabled Incentive-Driven Game Theoretic Approach for Data Sharing. IEEE Access, pages 1--1, 2024. [ bib | DOI | .pdf ]
[5] Matthias Bittner, Dominik Dallinger, Matthias Wess Daniel Schnöll, Maximilian Götzinger, and Axel Jantsch. Once-For-All Neural Architecture for Time Series Classification on Microcontroller Platforms. In Under submission, 2024. [ bib ]
[6] David Breuss, Karel Rusý, Maximilian Götzinger, and Axel Jantsch. Generation of Synthetic Image Anomalies for Analysis and Evaluation. In Proceedings of the International Conference on Intelligent Systems and Pattern Recognition, 2024. [ bib | .pdf ]
[7] Axel Jantsch, Swaroop Ghosh, Umit Ogras, and Pascal Meinerzhagen. ISLPED 2023: International Symposium on Low-Power Electronics and Design. IEEE Design & Test, 41(1):93--94, 2024. [ bib | DOI ]
[8] Martin Lechner and Axel Jantsch. Hardware-Aware Latency Pruning for Efficient Inference on Embedded GPUs. Under submission, 2024. [ bib ]
[9] Matthias Wess, Daniel Schnöll, Dominik Dallinger, Matthias Bittner, and Axel Jantsch. Conformal Prediction based Confidence for Latency Estimation of DNN Accelerators: A Black-box Approach. IEEE Access, 2024. [ bib | DOI | .pdf ]

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Friday, 20 September 2024, 07:26:01