Search Results - "Hehn, Thomas M."

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  1. 1

    End-to-End Learning of Decision Trees and Forests by Hehn, Thomas M., Kooij, Julian F. P., Hamprecht, Fred A.

    Published in International journal of computer vision (01-04-2020)
    “…Conventional decision trees have a number of favorable properties, including a small computational footprint, interpretability, and the ability to learn from…”
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    Journal Article
  2. 2

    Hearing What You Cannot See: Acoustic Vehicle Detection Around Corners by Schulz, Yannick, Mattar, Avinash Kini, Hehn, Thomas M., Kooij, Julian F. P.

    Published in IEEE robotics and automation letters (01-04-2021)
    “…This work proposes to use passive acoustic perception as an additional sensing modality for intelligent vehicles. We demonstrate that approaching vehicles…”
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    Journal Article
  3. 3

    Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps by Hehn, Thomas M., Orekondy, Tribhuvanesh, Shental, Ori, Behboodi, Arash, Bucheli, Juan, Doshi, Akash, Namgoong, June, Yoo, Taesang, Sampath, Ashwin, Soriaga, Joseph B.

    “…Estimating path loss for a transmitter-receiver location is key to many use-cases including network planning and handover. Machine learning has become a…”
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    Conference Proceeding
  4. 4

    Instance Stixels: Segmenting and Grouping Stixels into Objects by Hehn, Thomas M., Kooij, Julian F. P., Gavrila, Dariu M.

    “…State-of-the-art stixel methods fuse dense stereo and semantic class information, e.g. from a Convolutional Neural Network (CNN), into a compact representation…”
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    Conference Proceeding
  5. 5

    How do Cross-View and Cross-Modal Alignment Affect Representations in Contrastive Learning? by Hehn, Thomas M, Kooij, Julian F. P, Gavrila, Dariu M

    Published 23-11-2022
    “…Various state-of-the-art self-supervised visual representation learning approaches take advantage of data from multiple sensors by aligning the feature…”
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    Journal Article
  6. 6

    Transformer-Based Neural Surrogate for Link-Level Path Loss Prediction from Variable-Sized Maps by Hehn, Thomas M, Orekondy, Tribhuvanesh, Shental, Ori, Behboodi, Arash, Bucheli, Juan, Doshi, Akash, Namgoong, June, Yoo, Taesang, Sampath, Ashwin, Soriaga, Joseph B

    Published 06-10-2023
    “…Estimating path loss for a transmitter-receiver location is key to many use-cases including network planning and handover. Machine learning has become a…”
    Get full text
    Journal Article
  7. 7

    Hearing What You Cannot See: Acoustic Vehicle Detection Around Corners by Schulz, Yannick, Mattar, Avinash Kini, Hehn, Thomas M, Kooij, Julian F. P

    Published 25-02-2021
    “…This work proposes to use passive acoustic perception as an additional sensing modality for intelligent vehicles. We demonstrate that approaching vehicles…”
    Get full text
    Journal Article