5 citations · 30 across the 20 of their papers we have counts for
9 papers · 1 filter
A novel cluster internal evaluation index based on hyper-balls
Jiang Xie, Pengfei Zhao, Shuyin Xia +2
It is crucial to evaluate the quality and determine the optimal number of clusters in cluster analysis. In this paper, the multi-granularity characterization of the data set is car…
Granular-Ball Fuzzy Set and Its Implementation in SVM
Shuyin Xia, Xiaoyu Lian, Guoyin Wang +2
Most existing fuzzy set methods use points as their input, which is the finest granularity from the perspective of granular computing. Consequently, these methods are neither effic…
GBSVM: Granular-ball Support Vector Machine
Shuyin Xia, Xiaoyu Lian, Guoyin Wang +3
GBSVM (Granular-ball Support Vector Machine) is a significant attempt to construct a classifier using the coarse-to-fine granularity of a granular-ball as input, rather than a sing…
GBC: An Efficient and Adaptive Clustering Algorithm Based on Granular-Ball
Shuyin Xia, Jiang Xie, Guoyin Wang
Existing clustering methods are based on a single granularity of information, such as the distance and density of each data. This most fine-grained based approach is usually ineffi…
One-Stage Deep Edge Detection Based on Dense-Scale Feature Fusion and Pixel-Level Imbalance Learning
Dawei Dai, Chunjie Wang, Shuyin Xia +2
Edge detection, a basic task in the field of computer vision, is an important preprocessing operation for the recognition and understanding of a visual scene. In conventional model…
Multi-granularity Association Learning Framework for on-the-fly Fine-Grained Sketch-based Image Retrieval
Dawei Dai, Xiaoyu Tang, Shuyin Xia +3
Fine-grained sketch-based image retrieval (FG-SBIR) addresses the problem of retrieving a particular photo in a given query sketch. However, its widespread applicability is limited…
An Efficient and Accurate Rough Set for Feature Selection, Classification and Knowledge Representation
Shuyin Xia, Xinyu Bai, Guoyin Wang +4
This paper present a strong data mining method based on rough set, which can realize feature selection, classification and knowledge representation at the same time. Rough set has…
An Efficient and Adaptive Granular-ball Generation Method in Classification Problem
Shuyin Xia, Xiaochuan Dai, Guoyin Wang +2
Granular-ball computing is an efficient, robust, and scalable learning method for granular computing. The basis of granular-ball computing is the granular-ball generation method. T…
A Unified Granular-ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set
Shuyin Xia, Cheng Wang, Guoyin Wang +5
Pawlak rough set and neighborhood rough set are the two most common rough set theoretical models. Pawlak can use equivalence classes to represent knowledge, but it cannot process c…