Search Results for author: Christopher J. Holder

Found 4 papers, 0 papers with code

Building Resilience to Out-of-Distribution Visual Data via Input Optimization and Model Finetuning

no code implementations29 Nov 2022 Christopher J. Holder, Majid Khonji, Jorge Dias, Muhammad Shafique

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.

Autonomous Vehicles Semantic Segmentation

On Efficient Real-Time Semantic Segmentation: A Survey

no code implementations17 Jun 2022 Christopher J. Holder, Muhammad Shafique

Semantic segmentation is the problem of assigning a class label to every pixel in an image, and is an important component of an autonomous vehicle vision stack for facilitating scene understanding and object detection.

object-detection Object Detection +2

Depth Not Needed - An Evaluation of RGB-D Feature Encodings for Off-Road Scene Understanding by Convolutional Neural Network

no code implementations4 Jan 2018 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 surpass prior traditional feature driven approaches.

Autonomous Vehicles road scene understanding +3

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