◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Nima Tajbakhsh

36 papers hereh-index 2720.4k citations67 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author26
  • last author3

Across the 33 of 36 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.CV10
  • cs.LG7
  • eess.IV7
  • cs.AI1
  • cs.SE1

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedConvolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

3.3k citations · 3.5k across the 28 of their papers we have counts for

collaborators
Showing 2020Show all

3 papers · 1 filter

cs.CV2020★ 6 cited

Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts

Gaurav Fotedar, Nima Tajbakhsh, Shilpa Ananth +1

Supervised learning has proved effective for medical image analysis. However, it can utilize only the small labeled portion of data; it fails to leverage the large amounts of unlab…

eess.IV2020

Computer Aided Detection for Pulmonary Embolism Challenge (CAD-PE)

Germán González, Daniel Jimenez-Carretero, Sara Rodríguez-López +17

Rationale: Computer aided detection (CAD) algorithms for Pulmonary Embolism (PE) algorithms have been shown to increase radiologists' sensitivity with a small increase in specifici…

eess.IV2020★ 76 cited

UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation

Zongwei Zhou, Md Mahfuzur Rahman Siddiquee, Nima Tajbakhsh +1

The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.