Christophe Chesneau
researcher (ORCID 0000-0002-1522-9292)
Facts
6 properties- Instance of
- human
- Date of birth
- 1981
- Occupation
- researcher, university teacher, mathematician
- Given name
- Christophe[6]
- Maintained by WikiProject
- WikiProject Mathematics[7]
🏷️ Also known as
en Christophe Chesneau
🔖 Identifiers · 8
- ISNI
- 0000000139917084
- ORCID iD
- 0000-0002-1522-9292
- VIAF cluster ID
- 207170063
- GND ID
- 1065481829
- DDB person (GND) ID
- 1065481829
- HAL author ID
- christophe-chesneau
- IdRef ID
- 113793901
- ZbMATH author ID
- chesneau.christophe
🔗 Connections
Author of 23
A new class of probability distributions via cosine and sine functions with applications,
COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach,
Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches,
Discrimination of sunflower seeds using multispectral and texture dataset in combination with region selection and supervised classification methods,
Inverse power XLindley distribution with statistical inference and applications to engineering data,
Machine learning approach for the classification of corn seed using hybrid features,
Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image,
Machine-Learning Based Hybrid-Feature Analysis for Liver Cancer Classification Using Fused (MR and CT) Images
+15 more
← Authored by 23
A new class of probability distributions via cosine and sine functions with applications,
COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach,
Development of Nonlaboratory-Based Risk Prediction Models for Cardiovascular Diseases Using Conventional and Machine Learning Approaches,
Discrimination of sunflower seeds using multispectral and texture dataset in combination with region selection and supervised classification methods,
Inverse power XLindley distribution with statistical inference and applications to engineering data,
Machine learning approach for the classification of corn seed using hybrid features,
Machine Learning Based Automated Segmentation and Hybrid Feature Analysis for Diabetic Retinopathy Classification Using Fundus Image,
Machine-Learning Based Hybrid-Feature Analysis for Liver Cancer Classification Using Fused (MR and CT) Images
+15 more
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