ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1801.09449
  4. Cited By
TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D
  Segmentation using Sparse and Binary Convolutions

TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions

29 January 2018
M. Heinrich
Maximilian Blendowski
Ozan Oktay
    MedIm
ArXivPDFHTML

Papers citing "TernaryNet: Faster Deep Model Inference without GPUs for Medical 3D Segmentation using Sparse and Binary Convolutions"

3 / 3 papers shown
Title
Quantized Embedding Vectors for Controllable Diffusion Language Models
Quantized Embedding Vectors for Controllable Diffusion Language Models
Cheng Kang
Xinye Chen
Yong Hu
Daniel Novak
31
0
0
15 Feb 2024
Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and
  Future Directions
Going Deep in Medical Image Analysis: Concepts, Methods, Challenges and Future Directions
F. Altaf
Syed Mohammed Shamsul Islam
Naveed Akhtar
N. Janjua
OOD
29
200
0
15 Feb 2019
Attention U-Net: Learning Where to Look for the Pancreas
Attention U-Net: Learning Where to Look for the Pancreas
Ozan Oktay
Jo Schlemper
Loic Le Folgoc
M. J. Lee
M. Heinrich
...
Jingyu Sun
Nils Y. Hammerla
Bernhard Kainz
Ben Glocker
Daniel Rueckert
SSeg
39
4,949
0
11 Apr 2018
1