27 citations · 49 across the 8 of their papers we have counts for
6 papers · 1 filter
Vehicle detection from GSV imagery: Predicting travel behaviour for cycling and motorcycling using Computer Vision
Kyriaki, Kokka, Rahul Goel +7
Transportation influence health by shaping exposure to physical activity, air pollution and injury risk. Comparative data on cycling and motorcycling behaviours is scarce, particul…
TrafficCAM: A Versatile Dataset for Traffic Flow Segmentation
Zhongying Deng, Yanqi Chen, Lihao Liu +4
Traffic flow analysis is revolutionising traffic management. Qualifying traffic flow data, traffic control bureaus could provide drivers with real-time alerts, advising the fastest…
NorMatch: Matching Normalizing Flows with Discriminative Classifiers for Semi-Supervised Learning
Zhongying Deng, Rihuan Ke, Carola-Bibiane Schonlieb +1
Semi-Supervised Learning (SSL) aims to learn a model using a tiny labeled set and massive amounts of unlabeled data. To better exploit the unlabeled data the latest SSL methods use…
A Three-Stage Self-Training Framework for Semi-Supervised Semantic Segmentation
Rihuan Ke, Angelica Aviles-Rivero, Saurabh Pandey +2
Semantic segmentation has been widely investigated in the community, in which the state of the art techniques are based on supervised models. Those models have reported unprecedent…
Multi-task deep learning for image segmentation using recursive approximation tasks
Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis +3
Fully supervised deep neural networks for segmentation usually require a massive amount of pixel-level labels which are manually expensive to create. In this work, we develop a mul…
Learning to segment microscopy images with lazy labels
Rihuan Ke, Aurélie Bugeau, Nicolas Papadakis +2
The need for labour intensive pixel-wise annotation is a major limitation of many fully supervised learning methods for segmenting bioimages that can contain numerous object instan…