MIPPR 2023. XXXI : Parallel Processing of Images and Optimization Techniques; and Medical Imaging / edited by Jianguo Liu [and six others].

Format:

Book

Contributor:

Liu, Jianguo, editor.

Language:

English

Subjects (All):

Medical imaging equipment industry.

Multispectral imaging--Congresses.

Multispectral imaging.

Physical Description:

1 online resource (34 pages)

Place of Publication:

Wuhan, China : SPIE, 2024.

Summary:

The International Conference on Multispectral Image Processing and Pattern Recognition (MIPPR) is an international academic conference jointly organized by the International Society of Optical Engineering (SPIE) and China, and has successfully held eleven sessions. In 2019, the 11th International Symposium on Multispectral Image Processing and Pattern Recognition was held in Wuhan, China. This symposium was a great success. Scientists, engineers, and graduate students presented over 50 talks and 140 posters conveying latest research results in image processing and pattern recognition. As is known to all, Covid-19 damaged our convention of holding symposium every two years. The 12th International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR'2023) will be held again on November 10-12，2023 in Wuhan, Hubei, China. This means human being society has leaped out of the shadow of Covid-19. The conference will bring together scientists, professors, engineers and graduate students in this field and provide a forum for presentation, exchange and discussion of recent advances in theory, techniques, algorithms and applications in Multispectral Image Processing and Pattern Recognition. In order to better inform the participants of the latest developments in the different branches of multispectral image processing and pattern recognition, apart from general papers to be presented at the forthcoming conference, we shall organize several plenary sessions where the distinguished professors will present the keynote speeches. Wecome to Wuhan! Wecome to MIPPR2023!.

Contents:

Front Matter: Volume 13087; Medical Imaging and Processing; Contextual attention U-net: a deep learning-based model for decoding brain characteristics of smokers; He Deng, Xing Kuang, Fuchun Lin; A shape and texture feature blending network for bone marrow cells classification using auxiliary learning; Zhengyang Guo, Zengbiao Yang, Xuanyu Xiang, et al.; An improved depth reconstruction method for unstable illumination environments in endoscopic surgeries; Shaowu Peng, Zeqi Li.

Notes:

Description based on publisher supplied metadata and other sources.

Includes bibliographical references.

ISBN:

1-5106-7498-5