Search Results for author: Jinsol Lee

Found 5 papers, 0 papers with code

Open-Set Recognition with Gradient-Based Representations

no code implementations16 Jun 2022 Jinsol Lee, Ghassan AlRegib

Neural networks for image classification tasks assume that any given image during inference belongs to one of the training classes.

Image Classification Open Set Learning

Gradient-Based Adversarial and Out-of-Distribution Detection

no code implementations16 Jun 2022 Jinsol Lee, Mohit Prabhushankar, Ghassan AlRegib

We propose to utilize gradients for detecting adversarial and out-of-distribution samples.

Out-of-Distribution Detection

Gradients as a Measure of Uncertainty in Neural Networks

no code implementations18 Aug 2020 Jinsol Lee, Ghassan AlRegib

We demonstrate the effectiveness of gradients as a measure of model uncertainty in applications of detecting unfamiliar inputs, including out-of-distribution and corrupted samples.

Out-of-Distribution Detection

Object Recognition under Multifarious Conditions: A Reliability Analysis and A Feature Similarity-based Performance Estimation

no code implementations18 Feb 2019 Dogancan Temel, Jinsol Lee, Ghassan AlRegib

Experimental results show that deep learning-based image representations can estimate the recognition performance variation with a Spearman's rank-order correlation of 0. 94 under multifarious acquisition conditions.

Object Recognition

CURE-OR: Challenging Unreal and Real Environments for Object Recognition

no code implementations18 Oct 2018 Dogancan Temel, Jinsol Lee, Ghassan AlRegib

Moreover, we investigate the relationship between object recognition and image quality and show that objective quality algorithms can estimate recognition performance under certain photometric challenging conditions.

Computer Vision Object Recognition

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