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researcher

Michael W. Spratling

2 papers here

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

author position
  • last author2

Across the 2 of 2 papers where every author was matched, so the position is known.

fields
  • cs.CV1
  • cs.LG1

identity via Semantic Scholar / OpenAlex

most citedUnderstanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization

37 citations · 37 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2022★ 37 cited

Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization

Lin Li, Michael Spratling

Adversarial training is widely used to improve the robustness of deep neural networks to adversarial attack. However, adversarial training is prone to overfitting, and the cause is…

cs.CV2022

CobNet: Cross Attention on Object and Background for Few-Shot Segmentation

Haoyan Guan, Michael Spratling

Few-shot segmentation aims to segment images containing objects from previously unseen classes using only a few annotated samples. Most current methods focus on using object inform…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.