Jiankun Hu | The University of New South Wales (original) (raw)
Papers by Jiankun Hu
IEEE Transactions on Cloud Computing, Jul 1, 2021
IEEE Transactions on Computers, 2014
Future Generation Computer Systems, Aug 1, 2020
arXiv (Cornell University), Oct 8, 2018
IEEE Journal of Biomedical and Health Informatics, 2015
Future Generation Computer Systems, Feb 1, 2018
arXiv (Cornell University), Jun 26, 2022
arXiv (Cornell University), Sep 20, 2018
Proceedings. 2004 12th IEEE International Conference on Networks (ICON 2004) (IEEE Cat. No.04EX955)
IEEE Internet of Things Journal, 2021
IEEE Transactions on Dependable and Secure Computing, 2020
Journal of Parallel and Distributed Computing, 2020
Remote Sensing, 2019
Automatic weed detection and classification faces the challenges of large intraclass variation an... more Automatic weed detection and classification faces the challenges of large intraclass variation and high spectral similarity to other vegetation. With the availability of new high-resolution remote sensing data from various platforms and sensors, it is possible to capture both spectral and spatial characteristics of weed species at multiple scales. Effective multi-resolution feature learning is then desirable to extract distinctive intensity, texture and shape features of each category of weed to enhance the weed separability. We propose a feature extraction method using a Convolutional Neural Network (CNN) and superpixel based Local Binary Pattern (LBP). Both middle and high level spatial features are learned using the CNN. Local texture features from superpixel-based LBP are extracted, and are also used as input to Support Vector Machines (SVM) for weed classification. Experimental results on the hyperspectral and remote sensing datasets verify the effectiveness of the proposed met...
IEEE Transactions on Information Forensics and Security, 2019
2013 6th International Congress on Image and Signal Processing (CISP), 2013