Lmb.informatik.uni-freiburg.de - SEO Checker

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Overview of the SEO Check
Meta information
69% 
Page quality
37% 
Page structure
79% 
Link structure
25% 
Server
100% 
External factors
100% 
SEO Score
Response time
0.12 s
File size
46.70 kB
Words
986
Media files
125
Number of links
144 internal / 12 external

Task list of SEO Improvements

Meta specifications

Title
(Critically important)
Computer Vision Group, Freiburg
The length of the page title is perfect. (298 pixels out of 580 max pixel length)
There are no duplicate words in the title
Meta description
(Critically important)
The meta description is missing.
Crawlability
(Critically important)
There are no problems in accessing the website.
Canonical URL
(Important)
No canonical link is specified.
Language
(Somewhat important)
Language detected in text: en
Language defined in HTML: de
Server location: United States of America
The given language de does not conform with the detected language en.
The given language de does not conform with the detected language en.
Alternate/Hreflang Links
(Somewhat important)
There are no alternate links specified on this page.
Other meta tags
(Somewhat important)
There is no rel next meta tag on this page.
There is no rel prev meta tag on this page.
Domain
(Somewhat important)
This page is hosted on a subdomain. Use a top level domain for better SEO results.
The domain does not contain non-latin characters.
Page URL
(Somewhat important)
No parameters were found in the URL.
No session ID was found in the URL.
The URL does not have too many subdirectories.
Charset encoding
(Somewhat important)
The charset encoding (ISO-8859-1) is set correctly.
Doctype
(Nice to have)
The doctype XHTML 1.0 Transitional is set correctly.
The doctype is placed at first in the HTML code.
Favicon
(Nice to have)
The favicon is linked correctly.

Meta tags

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viewportwidth=device-width, initial-scale=1
robotsall
langde
X-UA-CompatibleIE=edge
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expires-1
pragmano-cache

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Page quality

Content
(Critically important)
The average number of words per sentence of 182 words is high.
This page contains 986 words. That's ok.
21.2% of the text are stop words.
Keywords used in the page title are also used in the page content. That's good!
The page contains a listing, which indicates a good text layout.
10 paragraphs were found on this page.
The text content is perfect.
No placeholders texts or images were found.
There are no duplicates on the site.
Frames
(Critically important)
This page does not use a frameset.
Mobile optimization
(Somewhat important)
No Apple touch icon is specified.
A viewport "width=device-width, initial-scale=1" is provided.
This page does not require any JavaScript files.
Bold and strong tags
(Somewhat important)
The usage of strong and bold tags is perfect. We recommend the use of up to 20 tags for this page.
Image SEO
(Somewhat important)
102 images have no alt attribute. The content of alt attributes is used by search engines.
Social Networks
(Nice to have)
There are only a few social sharing widgets on the page. Make your website popular in social networks with social sharing widgets.
Additional markup
(Nice to have)
No additional page markup was found.
HTTPS
(Somewhat important)
This website uses HTTPS to protect privacy and integrity of the exchanged data.
All included files are also transferred via HTTPS.

Media list

URLAlt attributeTitle
/css/home.pngHome
/css/unilogo.gifUni-Logo
/css/group_logo.pngLMB group logo
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/images/news_slideshow/RDB18.pngArtistic style transfer for videos and spherical images (IJCV 2018)
/images/news_slideshow/MIFDB18.pngWhat Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? (IJCV 2018)
/images/news_slideshow/BR18Data-Driven Modeling of Intracellular Auxin Fluxes Indicates a Dominant Role of the ER in Controlling Nuclear Auxin Uptake (Cell Reports 2018)
/images/news_slideshow/ZB183D Human Pose Estimation in RGBD Images for Robotic Task Learning (ICRA 2018)
/images/news_slideshow/Tat18.pngTangent Convolutions for Dense Prediction in 3D (CVPR 2018)
/images/news_slideshow/OB18.pngDPDB-Net: Exploiting Dense Connections for Convolutional Encoders (ICRA 2018)
...slideshow/octree-generating-networks.pngOctree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (ICCV 2017)
/images/news_slideshow/flownet2.pngFlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks (CVPR 2017)
...deshow/generating-chairs-tables-cars.pngLearning to Generate Chairs, Tables and Cars with Convolutional Networks (TPAMI 2017)
...ews_slideshow/cvpr2016-inverting-200.pngInverting Visual Representations with Convolutional Networks (CVPR 2016)
...deshow/cvpr2016-sceneflowdataset-200.pngA Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation (CVPR 2016)
...ews_slideshow/icra2016-bodyparts-200.pngDeep Learning for Human Part Discovery in Images (ICRA 2016)
...ews_slideshow/icra2016-bodyparts-200.pngDeep Learning for Human Part Discovery in Images (ICRA 2016)
/images/news_slideshow/ZOSB17a.pngChained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection (ICCV 2017)
/images/news_slideshow/IB17.pngEnd-to-End Learning of Video Super-Resolution with Motion Compensation (GCPR 2017)
/images/news_slideshow/SZB17a.pngOrientation-boosted voxel nets for 3D object recognition (BMVC 2017)
/images/news_slideshow/MR17.pngA new fate mapping system reveals context-dependent random or clonal expansion of microglia (Nature Neuroscience 2017)
/images/news_slideshow/UB17a.pngSparsity Invariant CNNs (3DV 2017)
/images/news_slideshow/UZUMIDB17.pngDeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)
/images/news_slideshow/UZUMIDB17.pngDeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)

Page structure

H1 heading
(Critically important)
There is no H1 heading specified.
Headings
(Important)
The structure of headings is missing one or more levels. Do not skip heading levels.

Heading structure

Heading levelContent
H2 Computer Vision Group
H3 News:
Some internal link anchor texts are too long.
Some internal links have dynamic parameters. All internal URLs, which are not marked as nofollow, should not contain dynamic parameters.
Some anchor texts are used more than once.
The number of internal links is ok.
There are 12 external links on this page.

Found links on this page

LinkAttributesAnchor text
/index.phpHome
/people/team.phpTeam
/people/social.phpSocial Events
/research/research.phpResearch
/PublicationsPublications
/lectures/teaching.phpTeaching
/resources/software.phpSoftware/Datasets
/jobs.phpJob Offers
/contact.phpContact
/interna/Internal
http://www.uni-freiburg.de/External Subdomain IMG-ALT Uni-Logo
A-TITLE Albert-Ludwigs-Universität Freiburg
/index.phpIMG-ALT LMB group logo
/index.phpPattern Recognition and Image Processing
http://www.informatik.uni-frei...External Subdomain Dept. of Computer Science
A-TITLE Dept. of Computer Science
http://www.tf.uni-freiburg.de/External Subdomain Faculty of Engineering
A-TITLE Technische Fakultät
/people/brox/index.en.htmlProf. Dr.-Ing. Thomas Brox
/people/brox/Thomas Brox
/people/ronneber/Olaf Ronneberger
/people/kortylew/Adam Kortylewski
/people/burkhardt/Hans Burkhardt
/people/willij/Julia Willi
/people/teister/Stefan Teister
/people/argusm/Max Argus
/people/bratulic/Jelena Bratulic
/people/bravoma/Maria Bravo
/people/dienertj/Johannes Dienert
/people/faridk/Karim Farid
/people/galessos/Silvio Galesso
/people/gings/Simon Ging
/people/hoffmann/David Hoffmann
/people/jesslen/Artur Jesslen
/people/mittal/Sudhanshu Mittal
/people/mousakha/Arian Mousakhan
/people/sahayr/Rajat Sahay
/people/schrodi/Simon Schrodi
/people/schroepp/Philipp Schröppel
/people/sommerl/Leonhard Sommer
/people/sunagad/Basavaraj Sunagad
/people/uhrigj/Jonas Uhrig
http://www.bioss.uni-freiburg.de/External Subdomain Centre for Biological Signalling Studies (BIOSS)
http://www.bioss.uni-freiburg.de/External Subdomain No Text
https://www.brainlinks-brainto...External Subdomain Cluster of Excellence BrainLinks BrainTools
https://www.brainlinks-brainto...External Subdomain No Text
http://erc.europa.eu/External Subdomain ERC Starting Grant
http://erc.europa.eu/External Subdomain No Text
/people/sahayrText duplicate Rajat Sahay
/people/sunagadText duplicate Basavaraj Sunagad
https://gvrl.mpi-inf.mpg.de/External Subdomain Adam Kortylewski's
/people/faridkText duplicate Karim Farid
https://www.iri.upc.edu/staff/...External Subdomain Mariella Dimiccoli
/Publications/?year=2024&artic...ECCV 2024
/Publications/?year=2024&artic...ICML 2024
/Publications/?year=2024&artic...CVPR 2024
/Publications/?year=2024&artic...ICRA 2024
/Publications/?year=2024&artic...ICLR 2024
/people/mousakhaText duplicate Arian Mousakhan
/Publications/?year=2023&artic...NeurIPS 2023
/Publications/2023/MB23aBest Paper Award
/Publications/?year=2023&artic...GCPR 2023
/Publications/?year=2023&artic...ICCV 2023
/people/bratulicText duplicate Jelena Bratulic
/people/mittalText duplicate Sudhanshu Mittal
/people/saikiatTonmoy Saikia
/people/dienertjText duplicate Johannes Dienert
/people/kortylewText duplicate Adam Kortylewski
/Publications/?year=2022&artic...GCPR 2022
/Publications/?year=2022&artic...ECCV 2022
/Publications/?year=2022&artic...3DV 2022
/Publications/?year=2022&artic...CVPR 2022
/people/schrodiText duplicate Simon Schrodi
/Publications/?year=2022&artic...AAAI 2022
/people/argusmText duplicate Max Argus
/Publications/?year=2022&artic...ICLR 2022
/people/boehmaAnton Boehm
/Publications/?year=2021&artic...ICCV 2021
/Publications/?year=2021&artic...MICCAI 2021
/people/gingsText duplicate Simon Ging
/people/cicekÖzgün Çiçek
/Publications/?year=2021&artic...CVPR 2021
/Publications/?year=2021&artic...ICLR 2020
/people/zimmermcChristian Zimmermann
/Publications/?year=2021&artic...NeurIPS 2020
/people/tatarchmMaxim Tatarchenko
/people/mayernNikolaus Mayer
/projects/flowcontrol/IROS
/people/hoffmannText duplicate David Hoffmann
/Publications/?year=2020&artic...CVPR
/people/ilgeEddy Ilg
/people/nimaNima Sedaghat
/Publications/?year=2020&artic...ISBI
/Publications/?year=2020&artic...ICLR
/Publications/?year=2020&artic...TPAMI
/people/bravomaMaría Bravo
/Publications/?year=2019&artic...ICCV
/Publications/?year=2019&artic...Text duplicate IROS
/Publications/?year=2019&artic...Text duplicate CVPR
/Publications/2019/Bro19ICML
/people/galessosText duplicate Silvio Galesso
/Publications/2019/BTF19Text duplicate ISBI
/people/bechtoljJan Bechtold
/people/schroeppText duplicate Philipp Schröppel
/Publications/2019/FMBCAMBBR19Nature Methods
/people/ummenhofBenjamin Ummenhofer
/people/abdulkaAhmed Abdulkadir
/people/gomezeEstibaliz Gómez
/Publications/?year=2018&artic...ECCV
/Publications/2018/AB18Text duplicate ICLR
/Publications/2018/UB18IV
/people/luyaoYao Lu
/people/makansioOsama Makansi
/Publications/2018/Tat18Text duplicate CVPR
/people/faciljmJosé Fácil
/Publications/?year=2018&artic...IJCV
/Publications/?year=2018&artic...ICRA
/people/mummadicChaithanya Kumar Mummadi
/people/mittalText duplicate Sudhanshu Mittal
/people/ruderaManuel Ruder
/people/benschRobert Bensch
/people/drayerBenjamin Drayer
/people/maidDominic Mai
/Publications/2017/UB17abest student paper
/people/team.phpPhilipp Fischer
https://news.tf.uni-freiburg.d...External Subdomain Wolfgang-Gentner-Nachwuchsförderpreis
/people/argusmText duplicate Max Argus
/people/marrakchYassine Marrakchi
/people/melbaumsSvenja Melbaum
/people/saikiatText duplicate Tonmoy Saikia
/Publications/2017/OB17aIJRR
/Publications/2017/SZB17aBMVC
/Publications/2017/MIB17GCPR
/Publications/2017/UB17/Text duplicate IJCV
/Publications/?year=2017&artic...Text duplicate CVPR
/Publications/2017/OB17ICRA paper
/Publications/2018/RDB18Artistic style transfer for videos and spherical images (IJCV 2018)
IMG-ALT Artistic style transfer for videos and spherical images (IJCV 2018)
/Publications/2018/MIFDB18What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? (IJCV 2018)
IMG-ALT What Makes Good Synthetic Training Data for Learning Disparity and Optical Flow Estimation? (IJCV 2018)
/Publications/2018/BR18Data-Driven Modeling of Intracellular Auxin Fluxes Indicates a Dominant Role of the ER in Controlling Nuclear Auxin Uptake (Cell Reports 2018)
IMG-ALT Data-Driven Modeling of Intracellular Auxin Fluxes Indicates a Dominant Role of the ER in Controlling Nuclear Auxin Uptake (Cell Reports 2018)
/Publications/2018/ZB183D Human Pose Estimation in RGBD Images for Robotic Task Learning (ICRA 2018)
IMG-ALT 3D Human Pose Estimation in RGBD Images for Robotic Task Learning (ICRA 2018)
/Publications/2018/Tat18Tangent Convolutions for Dense Prediction in 3D (CVPR 2018)
IMG-ALT Tangent Convolutions for Dense Prediction in 3D (CVPR 2018)
/Publications/2018/OB18DPDB-Net: Exploiting Dense Connections for Convolutional Encoders (ICRA 2018)
IMG-ALT DPDB-Net: Exploiting Dense Connections for Convolutional Encoders (ICRA 2018)
/Publications/2017/TDB17bOctree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (ICCV 2017)
IMG-ALT Octree Generating Networks: Efficient Convolutional Architectures for High-resolution 3D Outputs (ICCV 2017)
/Publications/2017/IMSKDB17FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks (CVPR 2017)
IMG-ALT FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks (CVPR 2017)
/Publications/2017/DTB17Learning to Generate Chairs, Tables and Cars with Convolutional Networks (TPAMI 2017)
IMG-ALT Learning to Generate Chairs, Tables and Cars with Convolutional Networks (TPAMI 2017)
/Publications/2017/DB16Inverting Visual Representations with Convolutional Networks (CVPR 2016)
IMG-ALT Inverting Visual Representations with Convolutional Networks (CVPR 2016)
/Publications/2017/MIFDB16A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation (CVPR 2016)
IMG-ALT A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation (CVPR 2016)
/Publications/2017/OB16aDeep Learning for Human Part Discovery in Images (ICRA 2016)
IMG-ALT Deep Learning for Human Part Discovery in Images (ICRA 2016)
/Publications/2017/OB16aText duplicate Deep Learning for Human Part Discovery in Images (ICRA 2016)
IMG-ALT Deep Learning for Human Part Discovery in Images (ICRA 2016)
/Publications/2017/ZOSB17aChained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection (ICCV 2017)
IMG-ALT Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection (ICCV 2017)
/Publications/2017/IB17End-to-End Learning of Video Super-Resolution with Motion Compensation (GCPR 2017)
IMG-ALT End-to-End Learning of Video Super-Resolution with Motion Compensation (GCPR 2017)
/Publications/2017/SZB17aOrientation-boosted voxel nets for 3D object recognition (BMVC 2017)
IMG-ALT Orientation-boosted voxel nets for 3D object recognition (BMVC 2017)
/Publications/2017/MR17A new fate mapping system reveals context-dependent random or clonal expansion of microglia (Nature Neuroscience 2017)
IMG-ALT A new fate mapping system reveals context-dependent random or clonal expansion of microglia (Nature Neuroscience 2017)
/Publications/2017/UB17aSparsity Invariant CNNs (3DV 2017)
IMG-ALT Sparsity Invariant CNNs (3DV 2017)
/Publications/2017/UZUMIDB17DeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)
IMG-ALT DeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)
/Publications/2017/UZUMIDB17Text duplicate DeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)
IMG-ALT DeMoN: Depth and Motion Network for Learning Monocular Stereo (CVPR 2017)
/impressum.phpWebmaster Disclaimer
A-TITLE Impressum
/privacy.phpDatenschutz
A-TITLE Privacy Policy
/impressum.php© Copyright 2011 – 2024, LMB, University of Freiburg
A-TITLE Impressum

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Performance
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The page response time is excellent with 0.12 seconds.
This page does not require any CSS files.
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The file size of the HTML document is fine (47 kB).

HTTP Response Header

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KeywordResultRecheck
Group54%Check
Freiburg54%Check
Vision Group52%Check
Computer Vision Group51%Check
Computer50%Check
Computer Vision50%Check
Computer Science43%Check
CVPR38%Check
Networks38%Check
ICRA38%Check
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