Computer Vision and Image Understanding : Cviu
Overview
Computer Vision and Image Understanding (CVIU) is a renowned journal that focuses on the latest advancements in computer vision and image processing. It covers a wide range of topics including image analysis, pattern recognition, machine learning, and visual perception. With its rigorous peer-review process, CVIU provides a platform for researchers and practitioners to share their innovative research and contribute to the field of computer vision.
Details
Details
Abbr.
Comput Vis Image Underst
Start
1995
End
Continuing
Frequency
Monthly, <1997- >
p-ISSN
1077-3142
Country
United States
Language
English
Metrics
Metrics
h-index / Ranks: 1374
152
SJR / Ranks: 2150
1420
CiteScore / Ranks: 1650
9.40
JIF / Ranks: 1882
4.5
Recent Articles
1.
Okorie A, Makrogiannis S
Comput Vis Image Underst
. 2023 Aug;
189.
PMID: 37622168
We propose an automatic region-based registration method for remote sensing imagery. In this method, we aim to register two images by matching region properties to address possible errors caused by...
2.
Li R, Shi P, Pelz J, Alm C, Haake A
Comput Vis Image Underst
. 2022 Sep;
151:138-152.
PMID: 36046501
Experts have a remarkable capability of locating, perceptually organizing, identifying, and categorizing objects in images specific to their domains of expertise. In this article, we present a hierarchical probabilistic framework...
3.
Tu L, Vicory J, Elhabian S, Paniagua B, Prieto J, Damon J, et al.
Comput Vis Image Underst
. 2020 Jan;
151:72-79.
PMID: 31983868
Statistical analysis of shape representations relies on having good correspondence across a population. Improving correspondence yields improved statistics. Point distribution models (PDMs) are often used to represent object boundaries. Skeletal...
4.
Tu Z, Zheng S, Yuille A
Comput Vis Image Underst
. 2017 Dec;
109(3):290-304.
PMID: 29269996
In this paper, we present an efficient and robust algorithm for shape matching, registration, and detection. The task is to geometrically transform a source shape to fit a target shape....
5.
Li L, Wang J, Lu W, Tan S
Comput Vis Image Underst
. 2017 Jun;
155:173-194.
PMID: 28603407
Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging...
6.
Lu C, Adluru N, Ling H, Zhu G, Latecki L
Comput Vis Image Underst
. 2017 Mar;
114(7):827-834.
PMID: 28250706
In this paper we propose a novel framework for contour based object detection from cluttered environments. Given a contour model for a class of objects, it is first decomposed into...
7.
Wang B, Prastawa M, Irimia A, Saha A, Liu W, Goh S, et al.
Comput Vis Image Underst
. 2016 Nov;
151:3-13.
PMID: 27818606
With the increasing use of efficient multimodal 3D imaging, clinicians are able to access longitudinal imaging to stage pathological diseases, to monitor the efficacy of therapeutic interventions, or to assess...
8.
Cassidy S, Stenger B, van Dongen L, Yanagisawa K, Anderson R, Wan V, et al.
Comput Vis Image Underst
. 2016 Jul;
148:193-200.
PMID: 27375348
Adults with Autism Spectrum Conditions (ASC) experience marked difficulties in recognising the emotions of others and responding appropriately. The clinical characteristics of ASC mean that face to face or group...
9.
Xu Z, Saha P, Dasgupta S
Comput Vis Image Underst
. 2015 Aug;
116(10):1060-1075.
PMID: 26236148
Scale is a widely used notion in computer vision and image understanding that evolved in the form of scale-space theory where the key idea is to represent and analyze an...
10.
Xie J, Fletcher E, Singh B, Carmichael O
Comput Vis Image Underst
. 2014 Aug;
117(9):1128-1137.
PMID: 25132791
Alzheimer's Disease (AD) is characterized by a stereotypical spatial pattern of hippocampus (HP) atrophy over time, but reliable and precise measurement of localized longitudinal change to individual HP in AD...