Skip to content

Anh Totti Nguyen

Associate Professor of Computer Science, Auburn University

  • Current Page Parent Research
  • Lab
  • Press
  • Work with me
  • Teaching
    • Courses
    • K-6 AI club
  • About
  • CV
  • Current Page Parent Research
  • Lab
  • Press
  • Work with me
  • Teaching
    • Courses
    • K-6 AI club
  • About
  • CV

Screenshot

May 2024 0

Given an input image (a) from an unseen class of Eastern Bluebird, PEEB misclassifies it into Indigo Bunting (b), a visually similar blue bird in CUB-200 (d). To add a new class for Eastern Bluebird to the 200-class list that PEEB considers when classifying, we clone the 12 textual descriptors of Indigo Bunting (b) and edit (- -▸) the descriptor of throat and wings (c) to reflect their identification features described on AllAboutBirds.org (“Male Eastern Bluebirds are vivid, deep blue above and rusty or brick-red on the throat and breast”). After the edit, PEEB correctly predicts the input image into Eastern Bluebird (softmax: 0.0445) out of 201 classes (c). That is, the dot product between the wings text descriptor and the same orange region increases from 0.57 to 0.74.

Share
  • Previous PEEB: Part-based Image Classifiers with an Explainable and Editable Language Bottleneck
What makes your ExtJS application run so slow ?
Ext JS Javascript Performance

What makes your ExtJS application run so slow ?

  • May 15, 2011
  • 13
Computer Vision Explainable AI

Visual correspondence-based explanations improve AI robustness and human-AI team accuracy

  • July 26, 2022
NLP

PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search

  • July 19, 2023
Computer Vision Explainable AI

gScoreCAM: What objects is CLIP looking at?

  • September 30, 2022

Anh Totti Nguyen © 2026. All Rights Reserved.

Powered by WordPress. Theme by Alx.