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cs.CV2022
Building Resilience to Out-of-Distribution Visual Data via Input Optimization and Model Finetuning
Christopher J. Holder, Majid Khonji, Jorge Dias +1
A major challenge in machine learning is resilience to out-of-distribution data, that is data that exists outside of the distribution of a model's training data. Training is often…
cs.CV2020
Camera Bias in a Fine Grained Classification Task
Philip T. Jackson, Stephen Bonner, Ning Jia +3
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a mode…
cs.CV2018
Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network
Christopher J. Holder, Toby P. Breckon, Xiong Wei
Scene understanding for autonomous vehicles is a challenging computer vision task, with recent advances in convolutional neural networks (CNNs) achieving results that notably surpa…