Cell phenotype classification using multi threshold uniform local ternary patterns in fluorescence microscope images-Reference-Cited by-同舟云学术

Cell phenotype classification using multi threshold uniform local ternary patterns in fluorescence microscope images

Published:2021-01-08 Issue:8 Volume:80 Page:12103-12116
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Fekri-Ershad Shervan^ORCID

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-020-10321-w.pdf

Reference23 articles.

1. 2D hela dataset, http://murphylab.web.cmu.edu/data/2Dhela_images_download.html, accessed 25 November 2019.

2. Boland MV, Murphy RF (2001) A neural network classifier capable of recognizing the patterns of all major subcellular structures in fluorescence microscope images of hela cells. Bioinformatics 17(12):1213–1223

3. Fekri-Ershad S (2019) Pap smear classification using combination of global significant value, texture statistical features and time series features. Multimed Tools Appl 78(22):31121–31136

4. Fekriershad S, Tajeripour F (2017) Color texture classification based on proposed impulse-noise resistant color local binary patterns and significant points selection algorithm. Sens Rev 37(1):33–42

5. Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In Proc. of IEEE Computer Society Conference on computer vision and pattern recognition 2:2169–2178

Cited by 21 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing computer image recognition with improved image algorithms;Scientific Reports;2024-06-14

2. A novel hybrid method for the registration of deformable medical images using common subregions;Multimedia Tools and Applications;2024-04-24

3. Enhancing Computer Image Recognition with Improved Image Algorithms;2024-04-23

4. TECD_Attention: Texture-enhanced and cross-domain attention modeling for visual place recognition;Computer Vision and Image Understanding;2024-03

5. LMFD: lightweight multi-feature descriptors for image stitching;Scientific Reports;2023-11-30