scholarly journals A reference map of sphingolipids in murine tissues

Cell Reports ◽  
2021 ◽  
Vol 35 (11) ◽  
pp. 109250
Author(s):  
Sneha Muralidharan ◽  
Mitsugu Shimobayashi ◽  
Shanshan Ji ◽  
Bo Burla ◽  
Michael N. Hall ◽  
...  
Keyword(s):  
Reference Map

scholarly journals Volumetric Density-Equalizing Reference Map with Applications

2021 ◽  
Vol 86 (3) ◽  
Author(s):  
Gary P. T. Choi ◽  
Chris H. Rycroft
Keyword(s):  
Volumetric Density ◽  
Reference Map

Organizing Search Results with a Reference Map

2012 ◽  
Vol 18 (12) ◽  
pp. 2546-2555 ◽  
Author(s):  
Arlind Nocaj ◽  
Ulrik Brandes
Keyword(s):  
Search Results ◽  
Reference Map

Construction of an intra-specific sweet cherry (Prunus avium L.) genetic linkage map and synteny analysis with the Prunus reference map

2008 ◽  
Vol 4 (4) ◽  
pp. 897-910 ◽  
Author(s):  
James W. Olmstead ◽  
Audrey M. Sebolt ◽  
Antonio Cabrera ◽  
Suneth S. Sooriyapathirana ◽  
Sue Hammar ◽  
...  
Keyword(s):  
Linkage Map ◽  
Genetic Linkage ◽  
Sweet Cherry ◽  
Genetic Linkage Map ◽  
Prunus Avium ◽  
Synteny Analysis ◽  
Reference Map ◽  
Prunus Avium L

A proteome reference map forVibrio cholerae El Tor

PROTEOMICS ◽  
2004 ◽  
Vol 4 (5) ◽  
pp. 1491-1504 ◽  
Author(s):  
Ana Coelho ◽  
Eidy de Oliveira Santos ◽  
Mauro Luiz da Hora Faria ◽  
Daniela Palermo de Carvalho ◽  
Marcia Regina Soares ◽  
...  
Keyword(s):  
Reference Map ◽  
El Tor

scholarly journals Coral reef detection using SAR/RADARSAT-1 images at Costa dos Corais, PE/AL, Brazil

2008 ◽  
Vol 56 (2) ◽  
pp. 85-96 ◽  
Author(s):  
Frederico de Moraes Rudorff ◽  
Douglas Francisco Marcolino Gherardi
Keyword(s):  
Image Segmentation ◽  
Coral Reefs ◽  
Speckle Noise ◽  
Unsupervised Classification ◽  
Error Matrix ◽  
Reduced Dimensions ◽  
Environmental Protection Area ◽  
Protection Area ◽  
Good Potential ◽  
Reference Map

The present work aimed to examine the potentials of SAR RADARSAT-1 images to detect emergent coral reefs at the Environmental Protection Area of "Costa dos Corais". Multi-view filters were applied and tested for speckle noise reduction. A digital unsupervised classification based on image segmentation was performed and the classification accuracy was evaluated by an error matrix built between the SAR image classification and a reference map obtained from a TM Landsat-5 classification. The adaptative filters showed the best results for speckle suppression and border preservation, especially the Kuan, Gamma MAP, Lee, Frost and Enhanced Frost filters. Small similarity and area thresholds (5 and 10, respectively) were used for the image segmentation due to the reduced dimensions and the narrow and elongated forms of the reefs. The classification threshold of 99% had a better user's accuracy, but a lower producer's accuracy because it is a more restrictive threshold; therefore, it may be possible that it had a greater omission on reef classification. The results indicate that SAR images have a good potential for the detection of emergent coral reefs.

A 9.1-kb Gap in the Genome Reference Map Is Shown to Be a Stable Deletion/Insertion Polymorphism of Ancestral Origin

Genomics ◽  
2002 ◽  
Vol 80 (6) ◽  
pp. 585-592 ◽  
Author(s):  
Renato Robledo ◽  
Sandro Orru ◽  
Antonella Sidoti ◽  
Rosella Muresu ◽  
Diane Esposito ◽  
...  
Keyword(s):  
Insertion Polymorphism ◽  
Ancestral Origin ◽  
Reference Map

U-Map: A Reference Map for Safe Handling of Runtime Uncertainties

2020 ◽  
pp. 227-241
Author(s):  
Nishanth Laxman ◽  
Chee Hung Koo ◽  
Peter Liggesmeyer
Keyword(s):  
Safe Handling ◽  
Reference Map

scholarly journals AUTOMATIC MRF-BASED REGISTRATION OF HIGH RESOLUTION SATELLITE VIDEO DATA

2016 ◽  
Vol III-1 ◽  
pp. 121-128 ◽  
Author(s):  
C. Platias ◽  
M. Vakalopoulou ◽  
K. Karantzalos
Keyword(s):  
High Resolution ◽  
Markov Random Fields ◽  
Video Data ◽  
Registration Accuracy ◽  
Registration Method ◽  
Computational Performance ◽  
Markov Random ◽  
Video Frames ◽  
Reference Map ◽  
The Cost

In this paper we propose a deformable registration framework for high resolution satellite video data able to automatically and accurately co-register satellite video frames and/or register them to a reference map/image. The proposed approach performs non-rigid registration, formulates a Markov Random Fields (MRF) model, while efficient linear programming is employed for reaching the lowest potential of the cost function. The developed approach has been applied and validated on satellite video sequences from Skybox Imaging and compared with a rigid, descriptor-based registration method. Regarding the computational performance, both the MRF-based and the descriptor-based methods were quite efficient, with the first one converging in some minutes and the second in some seconds. Regarding the registration accuracy the proposed MRF-based method significantly outperformed the descriptor-based one in all the performing experiments.

Sign in / Sign up

Export Citation Format

Share Document