Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Sarkhan Badirli"'
Autor:
Sarkhan Badirli, Christine Johanna Picard, George Mohler, Frannie Richert, Zeynep Akata, Murat Dundar
Publikováno v:
Methods in Ecology and Evolution, Vol 14, Iss 6, Pp 1515-1530 (2023)
Abstract Classifying insect species involves a tedious process of identifying distinctive morphological insect characters by taxonomic experts. Machine learning can harness the power of computers to potentially create an accurate and efficient method
Externí odkaz:
https://doaj.org/article/39f93a028ef84281aa5907499c90d579
Autor:
Matthew Parrish, Ella O’Connell, George Eckert, Jay Hughes, Sarkhan Badirli, Hakan Turkkahraman
Publikováno v:
Diagnostics, Vol 13, Iss 17, p 2729 (2023)
The aim of this study was to create a novel machine learning (ML) algorithm for predicting the post-pubertal mandibular length and Y-axis in females. Cephalometric data from 176 females with Angle Class I occlusion were used to train and test seven M
Externí odkaz:
https://doaj.org/article/a4252386b04a49dc823f18bd836deb01
Autor:
James Volovic, Sarkhan Badirli, Sunna Ahmad, Landon Leavitt, Taylor Mason, Surya Sruthi Bhamidipalli, George Eckert, David Albright, Hakan Turkkahraman
Publikováno v:
Diagnostics, Vol 13, Iss 17, p 2740 (2023)
In the field of orthodontics, providing patients with accurate treatment time estimates is of utmost importance. As orthodontic practices continue to evolve and embrace new advancements, incorporating machine learning (ML) methods becomes increasingl
Externí odkaz:
https://doaj.org/article/c54e4891c3ff4c40b6747023581d75c0
Publikováno v:
Diagnostics, Vol 13, Iss 16, p 2713 (2023)
The goal of this study was to create a novel machine learning (ML) model that can predict the magnitude and direction of pubertal mandibular growth in males with Class II malocclusion. Lateral cephalometric radiographs of 123 males at three time poin
Externí odkaz:
https://doaj.org/article/d94e69bc300946d99b07068a7e87124a
Autor:
Dongyan Yan, Zhe Sun, Jiyuan Fang, Shanshan Cao, Wenjie Wang, Xinyue Chang, Sarkhan Badirli, Haoda Fu, Yushi Liu
A critical task in single-cell RNA sequencing (scRNA-Seq) data analysis is to identify cell types from heterogeneous tissues. While the majority of classification methods demonstrated high performance in scRNA-Seq annotation problems, a robust and ac
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f67fe0ede852a9a68c4e130eb0594396
Publikováno v:
Computer Vision – ACCV 2022 ISBN: 9783031263507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e306f2327a46a1dba0debfc6f1c68910
https://doi.org/10.1007/978-3-031-26351-4_32
https://doi.org/10.1007/978-3-031-26351-4_32
Autor:
null Sarkhan Badirli, null Christine Johanna Picard, null George Mohler, null Frannie Richert, null Zeynep Akata, null Murat Dundar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ece6b5f74a380e3cb4b63bfa6e9cf335
https://doi.org/10.1111/2041-210x.14104/v3/response1
https://doi.org/10.1111/2041-210x.14104/v3/response1
Publikováno v:
ACM Transactions on Spatial Algorithms and Systems. 6:1-14
Detecting anomalous activity in human mobility data has a number of applications, including road hazard sensing, telematics-based insurance, and fraud detection in taxi services and ride sharing. In this article, we address two challenges that arise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db3be3356a624950ec2488208e9389d9
https://doi.org/10.1145/3385809
https://doi.org/10.1145/3385809
Insects represent a large majority of biodiversity on Earth, yet so few species are described. Describing new species typicallyrequires specific taxonomic expertise to identify morphological characters that distinguish it from other known species and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1442f309a204965ec1ec6c2a05296a3a
https://doi.org/10.21203/rs.3.rs-1099185/v1
https://doi.org/10.21203/rs.3.rs-1099185/v1
Insects represent a large majority of biodiversity on Earth, yet only 20% of the estimated 5.5 million insect species are currently described (1). While describing new species typically requires specific taxonomic expertise to identify morphological
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8670b39c85f66d1816a66bcfc584936b
https://doi.org/10.1101/2021.09.15.460492
https://doi.org/10.1101/2021.09.15.460492