Local Binary Pattern and Its Variants: Application to Face Analysis
| Autor: | Kidiyo Kpalma, Hua Lu, Joseph Ronsin, Vincent Débordès, Jade Lizé |
|---|---|
| Přispěvatelé: | Institut d'Électronique et des Technologies du numéRique (IETR), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), School of Physics and Electronics, Shandong Normal University, Institut d'Electronique et de Télécommunications de Rennes (IETR), Centre National de la Recherche Scientifique (CNRS)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES), Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Ecole Supérieure d'Electricité - SUPELEC (FRANCE)-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1) |
| Rok vydání: | 2020 |
| Předmět: |
Pathogen-associated molecular patterns (PAMPs)
Facial expression business.industry Local binary patterns Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Face analysis 020207 software engineering Pattern recognition 02 engineering and technology Tomato resistance to virus Hrip1 Facial recognition system Local structure Set (abstract data type) Tomato yellow leaf curl virus (TYLCV) ComputingMethodologies_PATTERNRECOGNITION Transcriptional and posttranscriptional regulation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | Advances in Smart Technologies Applications and Case Studies ISBN: 9783030531867 Advances in Smart Technologies: Applications and Case Studies-Selected Papers from the First International Conference on Smart Information and Communication Technologies, SmartICT 2019, September 26-28, 2019, Saidia, Morocco Advances in Smart Technologies: Applications and Case Studies-Selected Papers from the First International Conference on Smart Information and Communication Technologies, SmartICT 2019, September 26-28, 2019, Saidia, Morocco, pp.94-102, 2020, ⟨10.1007/978-3-030-53187-4_11⟩ |
| DOI: | 10.1007/978-3-030-53187-4_11 |
| Popis: | Source : First international Conference on Smart Information & Communication Technologies (SmartICT’19), 26-09-2019, Saidia, Maroc.; International audience; Unlabelled - Tomato yellow leaf curl virus (TYLCV) causes tremendous losses of tomato worldwide. An elicitor Hrip1, which produced by , can serve as a pathogen-associated molecular patterns (PAMPs) to trigger the immune defense response in . Here, we show that Hrip1 can be targeted to the extracellular space and significantly delayed the development of symptoms caused by TYLCV in tomato. In basis of RNA-seq profiling, we find that 1621 differential expression genes (DEGs) with the opposite expression patterns are enriched in plant response to biotic stress between Hrip1 treatment and TYLCV infection of tomato. Thirty-two known differential expression miRNAs with the opposite expression patterns are identified by small RNA sequencing and the target genes of these miRNAs are significantly enriched in phenylpropanoid biosynthesis, plant hormone signal transduction and peroxisome. Based on the Pearson correlation analysis, 13 negative and 21 positive correlations are observed between differential expression miRNAs and DEGs. These miRNAs, which act as a key mediator of tomato resistance to TYLCV induced by Hrip1, regulate the expression of phenylpropanoid biosynthesis and plant hormone signal transduction-related genes. Taken together, our results provide an insight into tomato resistance to TYLCV induced by PAMP at transcriptional and posttranscriptional levels. Supplementary information - The online version contains supplementary material available at 10.1007/s13205-022-03426-6. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|