Search Results for author: Steve Cruz

Found 6 papers, 3 papers with code

Enhanced Performance of Pre-Trained Networks by Matched Augmentation Distributions

no code implementations19 Jan 2022 Touqeer Ahmad, Mohsen Jafarzadeh, Akshay Raj Dhamija, Ryan Rabinowitz, Steve Cruz, Chunchun Li, Terrance E. Boult

Specifically, we demonstrate that running inference on the center crop of an image is not always the best as important discriminatory information may be cropped-off.

A Review of Open-World Learning and Steps Toward Open-World Learning Without Labels

1 code implementation25 Nov 2020 Mohsen Jafarzadeh, Akshay Raj Dhamija, Steve Cruz, Chunchun Li, Touqeer Ahmad, Terrance E. Boult

Open-world learning is related to but also distinct from a multitude of other learning problems and this paper briefly analyzes the key differences between a wide range of problems including incremental learning, generalized novelty discovery, and generalized zero-shot learning.

Generalized Zero-Shot Learning Image Classification +2

To Beta or Not To Beta: Information Bottleneck for DigitaL Image Forensics

no code implementations11 Aug 2019 Aurobrata Ghosh, Zheng Zhong, Steve Cruz, Subbu Veeravasarapu, Terrance E. Boult, Maneesh Singh

We propose an innovative method to formulate the issue of localizing manipulated regions in an image as a deep representation learning problem using the Information Bottleneck (IB), which has recently gained popularity as a framework for interpreting deep neural networks.

Image Forensics Representation Learning +1

Toward Open-Set Face Recognition

no code implementations3 May 2017 Manuel Günther, Steve Cruz, Ethan M. Rudd, Terrance E. Boult

In this paper, we address the widespread misconception that thresholding verification-like scores is a good way to solve the open-set face identification problem, by formulating an open-set face identification protocol and evaluating different strategies for assessing similarity.

Face Identification Face Recognition +2

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