Search Results for author: Zetao Chen

Found 6 papers, 2 papers with code

A Holistic Visual Place Recognition Approach using Lightweight CNNs for Significant ViewPoint and Appearance Changes

1 code implementation7 Nov 2018 Ahmad Khaliq, Shoaib Ehsan, Zetao Chen, Michael Milford, Klaus McDonald-Maier

This paper presents a lightweight visual place recognition approach, capable of achieving high performance with low computational cost, and feasible for mobile robotics under significant viewpoint and appearance changes.

Visual Place Recognition

Learning Deep Descriptors With Scale-Aware Triplet Networks

no code implementations CVPR 2018 Michel Keller, Zetao Chen, Fabiola Maffra, Patrik Schmuck, Margarita Chli

Research on learning suitable feature descriptors for Computer Vision has recently shifted to deep learning where the biggest challenge lies with the formulation of appropriate loss functions, especially since the descriptors to be learned are not known at training time.

weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming

1 code implementation11 Sep 2017 Inkyu Sa, Zetao Chen, Marija Popovic, Raghav Khanna, Frank Liebisch, Juan Nieto, Roland Siegwart

In this paper, we present an approach for dense semantic weed classification with multispectral images collected by a micro aerial vehicle (MAV).

General Classification Management

Deep Learning Features at Scale for Visual Place Recognition

no code implementations18 Jan 2017 Zetao Chen, Adam Jacobson, Niko Sunderhauf, Ben Upcroft, Lingqiao Liu, Chunhua Shen, Ian Reid, Michael Milford

The success of deep learning techniques in the computer vision domain has triggered a range of initial investigations into their utility for visual place recognition, all using generic features from networks that were trained for other types of recognition tasks.

Visual Place Recognition

Convolutional Neural Network-based Place Recognition

no code implementations6 Nov 2014 Zetao Chen, Obadiah Lam, Adam Jacobson, Michael Milford

Recently Convolutional Neural Networks (CNNs) have been shown to achieve state-of-the-art performance on various classification tasks.

General Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.