What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Optics
Fabrice Meriaudeau mainly investigates Artificial intelligence, Computer vision, Optics, Diabetic retinopathy and Segmentation.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Microaneurysm and Pattern recognition.
The Computer vision study combines topics in areas such as Retina, Optical coherence tomography and Fundus.
His work on Diabetic macular edema as part of general Diabetic retinopathy research is frequently linked to Population, bridging the gap between disciplines.
The concepts of his Segmentation study are interwoven with issues in Radiology, Prostate, Speckle pattern and Atlas.
His Support vector machine research focuses on subjects like Principal component analysis, which are linked to Bag-of-words model, Histogram of oriented gradients, Feature detection, Feature and Correlation.
His most cited work include:
- Exudate-based diabetic macular edema detection in fundus images using publicly available datasets. (210 citations)
- A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images (141 citations)
- Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research (129 citations)
What are the main themes of his work throughout his whole career to date?
Fabrice Meriaudeau focuses on Artificial intelligence, Computer vision, Segmentation, Pattern recognition and Optics.
His Artificial intelligence study deals with Retinal intersecting with Retina.
His study ties his expertise on Diabetic retinopathy together with the subject of Computer vision.
His Diabetic retinopathy research is multidisciplinary, incorporating elements of Computer-aided diagnosis and Fundus.
In his research, Prostate cancer and Prostate biopsy is intimately related to Magnetic resonance imaging, which falls under the overarching field of Segmentation.
His Pattern recognition study combines topics in areas such as Local binary patterns and Optical coherence tomography.
He most often published in these fields:
- Artificial intelligence (61.04%)
- Computer vision (43.87%)
- Segmentation (19.62%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (61.04%)
- Deep learning (6.81%)
- Computer vision (43.87%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Deep learning, Computer vision, Segmentation and Pattern recognition.
Fabrice Meriaudeau interconnects Retinal and Optical coherence tomography in the investigation of issues within Artificial intelligence.
His Deep learning study integrates concerns from other disciplines, such as Object detection and Medical imaging.
He has researched Computer vision in several fields, including Polarimetry and Refraction.
His Segmentation study which covers Prostate that intersects with Radiology.
His work carried out in the field of Pattern recognition brings together such families of science as Artificial neural network, Autoencoder and Speech recognition.
Between 2016 and 2021, his most popular works were:
- Indian Diabetic Retinopathy Image Dataset (IDRiD): A Database for Diabetic Retinopathy Screening Research (129 citations)
- Heart rate estimation using facial video: A review (58 citations)
- Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Optics
Fabrice Meriaudeau mainly focuses on Artificial intelligence, Computer vision, Deep learning, Pattern recognition and Optical coherence tomography.
His research on Artificial intelligence frequently links to adjacent areas such as Optic disc.
His work deals with themes such as Photoplethysmogram, Signal and Underwater vehicle, which intersect with Computer vision.
His Deep learning study also includes fields such as
- Grading, Medical physics and Diabetic retinopathy most often made with reference to Medical imaging,
- Segmentation which connect with Delayed enhancement and Ventricle.
In his work, Motion, Biometrics, Landmark and F1 score is strongly intertwined with Speech recognition, which is a subfield of Pattern recognition.
His work in Optical coherence tomography tackles topics such as Diabetic macular edema which are related to areas like Biomedical engineering, Disease, Database, Diabetic retinopathy screening and Disease severity.
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