From On-Road to Off: Transfer Learning within a Deep Convolutional Neural Network for Segmentation and Classification of Off-Road Scenes

Holder, C.J.; Breckon, T.P.; Wei, X.

doi:10.1007/978-3-319-46604-0_11

All Outputs (2)

Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction (2018)
Presentation / Conference Contribution
Holder, C., & Breckon, T. (2018, June). Learning to Drive: Using Visual Odometry to Bootstrap Deep Learning for Off-Road Path Prediction. Presented at The 29th Intelligent Vehicles Symposium (IEEE IV 2018)., Changshu, China

From On-Road to Off: Transfer Learning within a Deep Convolutional Neural Network for Segmentation and Classification of Off-Road Scenes (2016)
Presentation / Conference Contribution
Holder, C., Breckon, T., & Wei, X. (2016, December). From On-Road to Off: Transfer Learning within a Deep Convolutional Neural Network for Segmentation and Classification of Off-Road Scenes. Presented at European Conference on Computer Vision Workshops., Amsterdam, The Netherlands

Real-time road-scene understanding is a challenging computer vision task with recent advances in convolutional neural networks (CNN) achieving results that notably surpass prior traditional feature driven approaches. Here, we take an existing CNN arc... Read More about From On-Road to Off: Transfer Learning within a Deep Convolutional Neural Network for Segmentation and Classification of Off-Road Scenes.