Search Results for author: ZhenZhou Wang

Found 7 papers, 0 papers with code

Phase Sampling Profilometry

no code implementations10 Sep 2020 Zhenzhou Wang

Structured light 3D surface imaging is a school of techniques in which structured light patterns are used for measuring the depth map of the object.

Segmentation of the Left Ventricle by SDD double threshold selection and CHT

no code implementations21 Jul 2020 ZiHao Wang, ZhenZhou Wang

Automatic and robust segmentation of the left ventricle (LV) in magnetic resonance images (MRI) has remained challenging for many decades.

Classification General Classification +5

Active stereo vision three-dimensional reconstruction by RGB dot pattern projection and ray intersection

no code implementations30 Mar 2020 Yongcan Shuang, Zhenzhou Wang

Experimental results showed that the proposed approach could reconstruct the 3D shape of the object significantly more robustly than state of the art methods that include the widely used disparity based active stereo vision method, the time of flight method and the structured light method.

Bottleneck detection by slope difference distribution: a robust approach for separating overlapped cells

no code implementations11 Dec 2019 ZhenZhou Wang

The bottleneck points of the one-dimensional boundary is detected by SDD and then transformed back into two-dimensional bottleneck points.

valid

Contour Sparse Representation with SDD Features for Object Recognition

no code implementations13 Oct 2019 Zhenzhou Wang

The contour of the object is similar to the histogram of the image.

Clustering Gesture Recognition +6

A New Clustering Method Based on Morphological Operations

no code implementations25 May 2019 Zhenzhou Wang

We evaluate and compare the proposed method with state of the art clustering methods with different types of data.

Clustering

Deep learning for image segmentation: veritable or overhyped?

no code implementations16 Apr 2019 Zhenzhou Wang

Compared to the high accuracies achieved by deep learning in classifying limited categories in international vision challenges, the image segmentation accuracies achieved by deep learning in the same challenges are only about eighty percent.

General Classification Image Classification +3

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