Example of IPSJ Transactions on Computer Vision and Applications format
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Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format
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Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format Example of IPSJ Transactions on Computer Vision and Applications format
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open access Open Access

IPSJ Transactions on Computer Vision and Applications — Template for authors

Publisher: Springer
Categories Rank Trend in last 3 yrs
Computer Vision and Pattern Recognition #13 of 85 up up by 45 ranks
journal-quality-icon Journal quality:
High
calendar-icon Last 4 years overview: 45 Published Papers | 394 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 10/07/2020
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Related Journals

open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 8.6
SJR: 0.53
SNIP: 2.363
open access Open Access
recommended Recommended

IEEE

Quality:  
High
CiteRatio: 11.4
SJR: 1.005
SNIP: 2.547
open access Open Access
recommended Recommended

Springer

Quality:  
High
CiteRatio: 8.6
SJR: 0.86
SNIP: 1.676

Journal Performance & Insights

CiteRatio

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

A measure of average citations received per peer-reviewed paper published in the journal.

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

8.8

115% from 2019

CiteRatio for IPSJ Transactions on Computer Vision and Applications from 2016 - 2020
Year Value
2020 8.8
2019 4.1
2018 1.7
2017 1.0
2016 1.0
graph view Graph view
table view Table view

0.612

0% from 2019

SJR for IPSJ Transactions on Computer Vision and Applications from 2016 - 2020
Year Value
2020 0.612
2019 0.611
2018 0.2
2017 0.156
2016 0.149
graph view Graph view
table view Table view

1.787

22% from 2019

SNIP for IPSJ Transactions on Computer Vision and Applications from 2016 - 2020
Year Value
2020 1.787
2019 1.467
2018 0.854
2017 0.361
2016 0.604
graph view Graph view
table view Table view

insights Insights

  • CiteRatio of this journal has increased by 115% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

insights Insights

  • SJR of this journal has increased by 0% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 22% in last years.
  • This journal’s SNIP is in the top 10 percentile category.

IPSJ Transactions on Computer Vision and Applications

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Springer

IPSJ Transactions on Computer Vision and Applications

Approved by publishing and review experts on SciSpace, this template is built as per for IPSJ Transactions on Computer Vision and Applications formatting guidelines as mentioned in Springer author instructions. The current version was created on and has been used by 318 authors to write and format their manuscripts to this journal.

Imaging

i
Last updated on
09 Jul 2020
i
ISSN
1606-8610
i
Open Access
Yes
i
Sherpa RoMEO Archiving Policy
White faq
i
Plagiarism Check
Available via Turnitin
i
Endnote Style
Download Available
i
Citation Type
Author Year
(Blonder et al, 1982)
i
Bibliography Example
Beenakker CWJ (2006) Specular andreev reflection in graphene. Phys Rev Lett 97(6):067,007, URL 10.1103/PhysRevLett.97.067007

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.1186/S41074-017-0027-2
Visual SLAM algorithms: a survey from 2010 to 2016
Takafumi Taketomi1, Hideaki Uchiyama2, Sei Ikeda3

Abstract:

SLAM is an abbreviation for simultaneous localization and mapping, which is a technique for estimating sensor motion and reconstructing structure in an unknown environment. Especially, Simultaneous Localization and Mapping (SLAM) using cameras is referred to as visual SLAM (vSLAM) because it is based on visual information onl... SLAM is an abbreviation for simultaneous localization and mapping, which is a technique for estimating sensor motion and reconstructing structure in an unknown environment. Especially, Simultaneous Localization and Mapping (SLAM) using cameras is referred to as visual SLAM (vSLAM) because it is based on visual information only. vSLAM can be used as a fundamental technology for various types of applications and has been discussed in the field of computer vision, augmented reality, and robotics in the literature. This paper aims to categorize and summarize recent vSLAM algorithms proposed in different research communities from both technical and historical points of views. Especially, we focus on vSLAM algorithms proposed mainly from 2010 to 2016 because major advance occurred in that period. The technical categories are summarized as follows: feature-based, direct, and RGB-D camera-based approaches. read more read less

Topics:

Simultaneous localization and mapping (52%)52% related to the paper, Augmented reality (51%)51% related to the paper
View PDF
477 Citations
open accessOpen access Journal Article DOI: 10.1186/S41074-018-0039-6
Multi-view large population gait dataset and its performance evaluation for cross-view gait recognition
Noriko Takemura1, Yasushi Makihara1, Daigo Muramatsu1, Tomio Echigo2, Yasushi Yagi1

Abstract:

This paper describes the world’s largest gait database with wide view variation, the “OU-ISIR gait database, multi-view large population dataset (OU-MVLP)”, and its application to a statistically reliable performance evaluation of vision-based cross-view gait recognition. Specifically, we construct a gait dataset that include... This paper describes the world’s largest gait database with wide view variation, the “OU-ISIR gait database, multi-view large population dataset (OU-MVLP)”, and its application to a statistically reliable performance evaluation of vision-based cross-view gait recognition. Specifically, we construct a gait dataset that includes 10,307 subjects (5114 males and 5193 females) from 14 view angles ranging 0° −90°, 180° −270°. In addition, we evaluate various approaches to gait recognition which are robust against view angles. By using our dataset, we can fully exploit a state-of-the-art method requiring a large number of training samples, e.g., CNN-based cross-view gait recognition method, and we validate effectiveness of such a family of the methods. read more read less

Topics:

Gait (human) (67%)67% related to the paper
View PDF
239 Citations
open accessOpen access Journal Article DOI: 10.2197/IPSJTCVA.4.53
The OU-ISIR Gait Database Comprising the Treadmill Dataset

Abstract:

This paper describes a large-scale gait database comprising the Treadmill Dataset. The dataset focuses on variations in walking conditions and includes 200 subjects with 25 views, 34 subjects with 9 speed variations from 2km/h to 10km/h with a 1km/h interval, and 68 subjects with at most 32 clothes variations. The range of va... This paper describes a large-scale gait database comprising the Treadmill Dataset. The dataset focuses on variations in walking conditions and includes 200 subjects with 25 views, 34 subjects with 9 speed variations from 2km/h to 10km/h with a 1km/h interval, and 68 subjects with at most 32 clothes variations. The range of variations in these three factors is significantly larger than that of previous gait databases, and therefore, the Treadmill Dataset can be used in research on invariant gait recognition. Moreover, the dataset contains more diverse gender and ages than the existing databases and hence it enables us to evaluate gait-based gender and age group classification in more statistically reliable way. read more read less

Topics:

Preferred walking speed (52%)52% related to the paper
View PDF
193 Citations
open accessOpen access Journal Article DOI: 10.2197/IPSJTCVA.1.83
A Survey of Manifold Learning for Images
Robert Pless1, Richard Souvenir2

Abstract:

Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. Understanding this manifold is a key first step in understanding many sets of images, and manifold learning approaches have recently been used within many application domains, including face recognition, medical image segmen... Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. Understanding this manifold is a key first step in understanding many sets of images, and manifold learning approaches have recently been used within many application domains, including face recognition, medical image segmentation, gait recognition and hand-written character recognition. This paper attempts to characterize the special features of manifold learning on image data sets, and to highlight the value and limitations of these approaches. read more read less

Topics:

Manifold alignment (75%)75% related to the paper, Nonlinear dimensionality reduction (59%)59% related to the paper, Manifold (fluid mechanics) (58%)58% related to the paper, Image segmentation (54%)54% related to the paper, Facial recognition system (53%)53% related to the paper
112 Citations
open accessOpen access Journal Article DOI: 10.1186/S41074-017-0028-1
A survey of diminished reality: Techniques for visually concealing, eliminating, and seeing through real objects
Shohei Mori1, Sei Ikeda2, Hideo Saito1

Abstract:

In this paper, we review diminished reality (DR) studies that visually remove, hide, and see through real objects from the real world. We systematically analyze and classify publications and present a technology map as a reference for future research. We also discuss future directions, including multimodal diminished reality.... In this paper, we review diminished reality (DR) studies that visually remove, hide, and see through real objects from the real world. We systematically analyze and classify publications and present a technology map as a reference for future research. We also discuss future directions, including multimodal diminished reality. We believe that this paper will be useful mainly for students who are interested in DR, beginning DR researchers, and teachers who introduce DR in their classes. read more read less

Topics:

Computer-mediated reality (69%)69% related to the paper, Augmented reality (63%)63% related to the paper
View PDF
102 Citations
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Frequently asked questions

1. Can I write IPSJ Transactions on Computer Vision and Applications in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the IPSJ Transactions on Computer Vision and Applications guidelines and auto format it.

2. Do you follow the IPSJ Transactions on Computer Vision and Applications guidelines?

Yes, the template is compliant with the IPSJ Transactions on Computer Vision and Applications guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in IPSJ Transactions on Computer Vision and Applications?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the IPSJ Transactions on Computer Vision and Applications citation style.

4. Can I use the IPSJ Transactions on Computer Vision and Applications templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for IPSJ Transactions on Computer Vision and Applications.

5. Can I use a manuscript in IPSJ Transactions on Computer Vision and Applications that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper IPSJ Transactions on Computer Vision and Applications that you can download at the end.

6. How long does it usually take you to format my papers in IPSJ Transactions on Computer Vision and Applications?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in IPSJ Transactions on Computer Vision and Applications.

7. Where can I find the template for the IPSJ Transactions on Computer Vision and Applications?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IPSJ Transactions on Computer Vision and Applications's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the IPSJ Transactions on Computer Vision and Applications's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. IPSJ Transactions on Computer Vision and Applications an online tool or is there a desktop version?

SciSpace's IPSJ Transactions on Computer Vision and Applications is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

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Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like IPSJ Transactions on Computer Vision and Applications?”

11. What is the output that I would get after using IPSJ Transactions on Computer Vision and Applications?

After writing your paper autoformatting in IPSJ Transactions on Computer Vision and Applications, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is IPSJ Transactions on Computer Vision and Applications's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for IPSJ Transactions on Computer Vision and Applications?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for IPSJ Transactions on Computer Vision and Applications. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In IPSJ Transactions on Computer Vision and Applications?

The 5 most common citation types in order of usage for IPSJ Transactions on Computer Vision and Applications are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the IPSJ Transactions on Computer Vision and Applications?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per IPSJ Transactions on Computer Vision and Applications's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download IPSJ Transactions on Computer Vision and Applications in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in IPSJ Transactions on Computer Vision and Applications Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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