《Siam Journal On Imaging Sciences》是一本以English為主的未開放獲取國際優(yōu)秀期刊,中文名稱暹羅影像科學(xué)雜志,本刊主要出版、報道數(shù)學(xué)-IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY領(lǐng)域的研究動態(tài)以及在該領(lǐng)域取得的各方面的經(jīng)驗和科研成果,介紹該領(lǐng)域有關(guān)本專業(yè)的最新進展,探討行業(yè)發(fā)展的思路和方法,以促進學(xué)術(shù)信息交流,提高行業(yè)發(fā)展。該刊已被國際權(quán)威數(shù)據(jù)庫SCIE收錄,為該領(lǐng)域相關(guān)學(xué)科的發(fā)展起到了良好的推動作用,也得到了本專業(yè)人員的廣泛認可。該刊最新影響因子為2.1,最新CiteScore 指數(shù)為3.8。
英文介紹
Siam Journal On Imaging Sciences雜志英文介紹
SIAM Journal on Imaging Sciences (SIIMS) covers all areas of imaging sciences, broadly interpreted. It includes image formation, image processing, image analysis, image interpretation and understanding, imaging-related machine learning, and inverse problems in imaging; leading to applications to diverse areas in science, medicine, engineering, and other fields. The journal’s scope is meant to be broad enough to include areas now organized under the terms image processing, image analysis, computer graphics, computer vision, visual machine learning, and visualization. Formal approaches, at the level of mathematics and/or computations, as well as state-of-the-art practical results, are expected from manuscripts published in SIIMS. SIIMS is mathematically and computationally based, and offers a unique forum to highlight the commonality of methodology, models, and algorithms among diverse application areas of imaging sciences. SIIMS provides a broad authoritative source for fundamental results in imaging sciences, with a unique combination of mathematics and applications.
SIIMS covers a broad range of areas, including but not limited to image formation, image processing, image analysis, computer graphics, computer vision, visualization, image understanding, pattern analysis, machine intelligence, remote sensing, geoscience, signal processing, medical and biomedical imaging, and seismic imaging. The fundamental mathematical theories addressing imaging problems covered by SIIMS include, but are not limited to, harmonic analysis, partial differential equations, differential geometry, numerical analysis, information theory, learning, optimization, statistics, and probability. Research papers that innovate both in the fundamentals and in the applications are especially welcome. SIIMS focuses on conceptually new ideas, methods, and fundamentals as applied to all aspects of imaging sciences.