Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ivan Khokhlov"'
Autor:
Ivan Khokhlov, Leonid Legashev, Irina Bolodurina, Alexander Shukhman, Daniil Shoshin, Svetlana Kolesnik
Publikováno v:
Toxics, Vol 12, Iss 10, p 750 (2024)
Predicting the toxicity of nanoparticles plays an important role in biomedical nanotechnologies, in particular in the creation of new drugs. Safety analysis of nanoparticles can identify potentially harmful effects on living organisms and the environ
Externí odkaz:
https://doaj.org/article/c53d4d21b2f44bd891b8fa08e80d87be
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Abstract We developed a Transformer-based artificial neural approach to translate between SMILES and IUPAC chemical notations: Struct2IUPAC and IUPAC2Struct. The overall performance level of our model is comparable to the rule-based solutions. We pro
Externí odkaz:
https://doaj.org/article/1ab182b42dd9410f8a7644dd9fb5bc4f
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030986810
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7695e5f730230f1229e1a11bde8a8668
https://doi.org/10.1007/978-3-030-98682-7_21
https://doi.org/10.1007/978-3-030-98682-7_21
Publikováno v:
Chemistry–Methods. 2
Autor:
Ivan Khokhlov, Mikhail Zertsalov
Publikováno v:
Russian journal of transport engineering. 8
Interaction peculiarities of a single unit bored pile with the surrounding rock mass under the horizontal load effect, as well as loss mechanism of piles bearing capacity, are considered. The article presents the numerical modeling results and a meth
The rise of deep learning in various scientific and technology areas promotes the development of AI-based tools for information retrieval. Optical recognition of organic structures is a key part of the automated extraction of chemical information. Ho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f70c7f3a35d831d0e920edf23adda00c
https://doi.org/10.26434/chemrxiv.14602716.v1
https://doi.org/10.26434/chemrxiv.14602716.v1
Supplementary information for the paper: Image2SMILES: Transformer-based Molecular Optical Recognition Engine examples_of_generated_training_images.jpg-examples of generated training images. examples_of_generated_training_images_for_molecules_with_va
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::298ff06c3b94a193cd6cff6809456735
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
We developed a Transformer-based artificial neural approach to translate between SMILES and IUPAC chemical notations: Struct2IUPAC and IUPAC2Struct. The overall performance level of our model is comparable to the rule-based solutions. We proved that
Providing IUPAC chemical names is necessary for chemical information exchange. We developed a Transformer-based artificial neural architecture to translate between SMILES and IUPAC chemical notations: Struct2IUPAC and IUPAC2Struct. Our models demonst
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2a5c760b7ac15d42693d4b40b2400208
https://doi.org/10.26434/chemrxiv.13274732.v2
https://doi.org/10.26434/chemrxiv.13274732.v2
Supplementary information for the paper (Struct2IUPAC: A transformer-based model for chemical names generation). opsin_fails.csv-- Structures that have been processed by OPSIN incorrectly. reverse_model_fails.csv-- Structures that have been processed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d0a8b18fc76103b5abfe591305b7c217