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C. Mattjie

3 papers hereh-index 499 citations21 works total

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

author position
  • first author1
  • middle author2

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.LG2
  • cs.CV1

identity via Semantic Scholar / OpenAlex

most citedZero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines

6 citations · 6 across the 3 of their papers we have counts for

collaborators

3 papers

cs.LG2026

Low-Rank Adapters Initialization via Gradient Surgery for Continual Learning

Joana Pasquali, Ramiro N. Barros, Arthur S. Bianchessi +7

LoRA is widely adopted for continual fine-tuning of Large Language Models due to its parameter efficiency, modularity across tasks, and compatibility with replay strategies. Howeve…

cs.LG2026

Inference-Time Machine Unlearning via Gated Activation Redirection

Vinícius Conte Turani, Otávio Parraga, João Vitor Boer Abitante +7

Large Language Models memorize vast amounts of training data, raising concerns regarding privacy, copyright infringement, and safety. Machine unlearning seeks to remove the influen…

cs.CV2023★ 6 cited

Zero-shot performance of the Segment Anything Model (SAM) in 2D medical imaging: A comprehensive evaluation and practical guidelines

Christian Mattjie, Luis Vinicius de Moura, Rafaela Cappelari Ravazio +4

Segmentation in medical imaging is a critical component for the diagnosis, monitoring, and treatment of various diseases and medical conditions. Presently, the medical segmentation…

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