output
20112026
most citedREFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs

858 citations

Showing 2015Show all

8 papers · 1 filter

cs.CV2015★ 4 cited

Fine-Grained Classification via Mixture of Deep Convolutional Neural Networks

ZongYuan Ge, Alex Bewley, Christopher McCool +3

We present a novel deep convolutional neural network (DCNN) system for fine-grained image classification, called a mixture of DCNNs (MixDCNN). The fine-grained image classification…

cs.CV2015★ 122 cited

Fast detection of multiple objects in traffic scenes with a common detection framework

Qichang Hu, Sakrapee Paisitkriangkrai, Chunhua Shen +2

Traffic scene perception (TSP) aims to real-time extract accurate on-road environment information, which in- volves three phases: detection of objects of interest, recognition of d…

cs.CV2015★ 1 cited

Dictionary Learning and Sparse Coding for Third-order Super-symmetric Tensors

Piotr Koniusz, Anoop Cherian

Super-symmetric tensors - a higher-order extension of scatter matrices - are becoming increasingly popular in machine learning and computer vision for modelling data statistics, co…

cs.CV2015★ 5 cited

On the Importance of Normalisation Layers in Deep Learning with Piecewise Linear Activation Units

Zhibin Liao, Gustavo Carneiro

Deep feedforward neural networks with piecewise linear activations are currently producing the state-of-the-art results in several public datasets. The combination of deep learning…

cs.RO2015★ 10 cited

Place Categorization and Semantic Mapping on a Mobile Robot

Niko Sünderhauf, Feras Dayoub, Sean McMahon +6

In this paper we focus on the challenging problem of place categorization and semantic mapping on a robot without environment-specific training. Motivated by their ongoing success…

cs.CV2015★ 8 cited

Efficient SDP Inference for Fully-connected CRFs Based on Low-rank Decomposition

Peng Wang, Chunhua Shen, Anton van den Hengel

Conditional Random Fields (CRF) have been widely used in a variety of computer vision tasks. Conventional CRFs typically define edges on neighboring image pixels, resulting in a sp…