mlsanityData to 14 Oct 2026

Assessing unconstrained surgical cuttings in VR using CNNs

arXiv 2205.00934 ↗First posted 2 May 2022cs.CV cs.AI cs.GRcited by 0

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Abstract (arXiv)

We present a Convolutional Neural Network (CNN) suitable to assess unconstrained surgical cuttings, trained on a dataset created with a data augmentation technique.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 10 references that are in the map. First posted on arXiv 2 May 2022.

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6 of 10 references.

References · 6

  1. 2016Time Series Classification from Scratch with Deep Neural Networks: A Strong Baselinecited by 360
  2. 2019ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernelscited by 339
  3. 2021A Survey on Deep Semi-supervised Learningcited by 251
  4. 2020Time Series Data Augmentation for Neural Networks by Time Warping with a Discriminative Teachercited by 22
  5. 2021An All-In-One Geometric Algorithm for Cutting, Tearing, and Drilling Deformable Modelscited by 2
  6. 2020MAGES 3.0: Tying the knot of medical VRcited by 1

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