Zobrazeno 1 - 10
of 29
pro vyhledávání: '"JingXin Liang"'
Publikováno v:
Computers, Vol 12, Iss 8, p 150 (2023)
Knowing the correct positioning of the tongue and mouth for pronunciation is crucial for learning English pronunciation correctly. Articulatory animation is an effective way to address the above task and helpful to English learners. However, articula
Externí odkaz:
https://doaj.org/article/ec53de46f6684fc4a67d536b4d629a94
Autor:
Yang Liu, Jingxin Liang
Publikováno v:
Frontiers in Business, Economics and Management. 7:245-254
The complexity of supply chain network structure makes the risk propagation among the enterprises in the supply chain more and more complicated. This paper constructs a SEIR risk propagation model for complex supply chain networks based on the analyt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8058ad0e9a3c466e7c02a7723d59bcf0
https://doi.org/10.54097/fbem.v7i3.5586
https://doi.org/10.54097/fbem.v7i3.5586
Publikováno v:
Electronics; Volume 11; Issue 17; Pages: 2663
Students’ actual learning engagement in class, which we call learning attention, is a major indicator used to measure learning outcomes. Obtaining and analyzing students’ attention accurately in offline classes is important empirical research tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4e070d1b9e4836644b39ba040c62098
https://doi.org/10.3390/electronics11172663
https://doi.org/10.3390/electronics11172663
Publikováno v:
ICCAI
This paper proposes a facial expression recognition system for smart learning on classroom. Firstly, YOLO is used to extract face images of multiple students from high-resolution video; secondly, face images are preprocessed, then a self-attention ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::401d1ca7896067eec5d139936c791d67
https://doi.org/10.1145/3467707.3467733
https://doi.org/10.1145/3467707.3467733
Publikováno v:
ICCAI
We present a self-attention-based method termed as Vision Transformer (ViT) to efficiently classify the human facial expressions. Our work can be divided into two contributions. First, the facial expression image is divided to N*N patches, each of wh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::058f2a49a9c9e4722aa15ecb40903e7e
https://doi.org/10.1145/3467707.3467735
https://doi.org/10.1145/3467707.3467735
Publikováno v:
Journal of Physics: Conference Series. 2002:012039
A self-attention-based method termed as Vision Transformer (ViT) is applied to efficiently detect the Surface Defects of Steel Plate. The defect image is divided to N*N patches, each of which corresponds to a word, and the whole image data is used as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::91968530076caf42664b17935579c973
https://doi.org/10.1088/1742-6596/2002/1/012039
https://doi.org/10.1088/1742-6596/2002/1/012039
Publikováno v:
Journal of Physics: Conference Series. 2002:012068
Abstracts. In this paper, ViT deep neural network based on self-attention mechanism is used in classification for images of soybean and weeds. Firstly, the overall image is split into multiple tiles; with each tile regarded as a word, the whole image
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45f755ace5a41517756cc6b92f1bc6f4
https://doi.org/10.1088/1742-6596/2002/1/012068
https://doi.org/10.1088/1742-6596/2002/1/012068
Plasmodium falciparum is the most lethal species of malaria. In infected human red blood cells, P. falciparum digests hemoglobin as a nutrient source, liberating cytotoxic free heme in the process. Sequestration and subsequent conversion of this bypr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cf13554db5f8d29df62040ede2db2fa8
https://resolver.caltech.edu/CaltechAUTHORS:20190729-100027029
https://resolver.caltech.edu/CaltechAUTHORS:20190729-100027029
Autor:
Amy M McCarthy-Torrens, Bert T. Lai, Matthew B. Coppock, James R. Heath, Carmen M Warren, Heather D. Agnew, Matthew N. Idso, JingXin Liang
Protein-catalyzed capture agents (PCCs) are synthetic and modular peptide-based affinity agents that are developed through the use of single generation in situ click chemistry screens against large peptide libraries. In such screens, the target prote
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::aa9a82f1f1a22c0296330cb5adf367c5
https://europepmc.org/articles/PMC6731165/
https://europepmc.org/articles/PMC6731165/
Autor:
John E. Heath, JingXin Liang, Jungwoo Kim, Emma Winson, Amy McCarthy, Joseph J. Oh, Ryan K. Henning, A. Katrine Museth, James R. Heath, Sunga Hong
Publikováno v:
Analytical chemistry. 90(15)
Protein catalyzed capture (PCC) agents are synthetic antibody surrogates that can target a wide variety of biologically relevant proteins. As a step towards developing a high-throughput PCC pipeline we report on the preparation of a barcoded rapid as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eaf4ecd5d6442622eba55437d75be8c8
https://pubmed.ncbi.nlm.nih.gov/29979578
https://pubmed.ncbi.nlm.nih.gov/29979578