Intelligence Science and Big Data Engineering. Big Data and Machine Learning Techniques [electronic resource] : 5th International Conference, IScIDE 2015, Suzhou, China, June 14-16, 2015, Revised Selected Papers, Part II /

Contributor(s):

Material type: Text

TextSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 9243Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XIX, 627 p. 205 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319238623

Subject(s):

Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:

006.37 23

LOC classification:

TA1634

Online resources:

Click here to access online

In: Springer Nature eBookSummary: The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

No physical items for this record

The two-volume set LNCS 9242 + 9243 constitutes the proceedings of the 5th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2015, held in Suzhou, China, in June 2015. The total of 126 papers presented in the proceedings was carefully reviewed and selected from 416 submissions. They deal with big data, neural networks, image processing, computer vision, pattern recognition and graphics, object detection, dimensionality reduction and manifold learning, unsupervised learning and clustering, anomaly detection, semi-supervised learning.

There are no comments on this title.

to post a comment.