activity
20192021
most citedUnsupervised Deep Features for Privacy Image Classification

15 citations · 16 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV20211 cited

Chaotic-to-Fine Clustering for Unlabeled Plant Disease Images

Uno Fang, Jianxin Li, Xuequan Lu +3

Current annotation for plant disease images depends on manual sorting and handcrafted features by agricultural experts, which is time-consuming and labour-intensive. In this paper,…

cs.CV2020

HDF: Hybrid Deep Features for Scene Image Representation

Chiranjibi Sitaula, Yong Xiang, Anish Basnet +2

Nowadays it is prevalent to take features extracted from pre-trained deep learning models as image representations which have achieved promising classification performance. Existin…

cs.CV201915 cited

Unsupervised Deep Features for Privacy Image Classification

Chiranjibi Sitaula, Yong Xiang, Sunil Aryal +1

Sharing images online poses security threats to a wide range of users due to the unawareness of privacy information. Deep features have been demonstrated to be a powerful represent…

cs.CV2019

Tag-based Semantic Features for Scene Image Classification

Chiranjibi Sitaula, Yong Xiang, Anish Basnet +2

The existing image feature extraction methods are primarily based on the content and structure information of images, and rarely consider the contextual semantic information. Regar…

cs.CV2019

Indoor image representation by high-level semantic features

Chiranjibi Sitaula, Yong Xiang, Yushu Zhang +2

Indoor image features extraction is a fundamental problem in multiple fields such as image processing, pattern recognition, robotics and so on. Nevertheless, most of the existing f…