Marc Souchaud

Cergy, 95000, France

Last Updated: 09/26/2026

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Found 10 publications

Application of wings interferential patterns (WIPs) and deep learning (DL) to classify some Culex. spp (Culicidae) of medical or veterinary importance.

Application of wings interferential patterns (WIPs) and deep learning (DL) to classify some Culex. spp (Culicidae) of medical or veterinary importance.

Journal: Scientific reports

Published: November 28, 2024

Toward automated small bowel capsule endoscopy reporting using a summarizing machine learning algorithm: The SUM UP study.

Toward automated small bowel capsule endoscopy reporting using a summarizing machine learning algorithm: The SUM UP study.

Journal: Clinics and research in hepatology and gastroenterology

Published: September 25, 2024

Species identification of phlebotomine sandflies using deep learning and wing interferential pattern (WIP).

Species identification of phlebotomine sandflies using deep learning and wing interferential pattern (WIP).

Journal: Scientific reports

Published: June 21, 2023

Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species.

Deep learning and wing interferential patterns identify Anopheles species and discriminate amongst Gambiae complex species.

Journal: Scientific reports

Published: June 20, 2023

An annotated wing interferential pattern dataset of dipteran insects of medical interest for deep learning.

An annotated wing interferential pattern dataset of dipteran insects of medical interest for deep learning.

Journal: Scientific data

Published: June 19, 2023

Wing Interferential Patterns (WIPs) and machine learning for the classification of some Aedes species of medical interest.

Wing Interferential Patterns (WIPs) and machine learning for the classification of some Aedes species of medical interest.

Journal: Scientific reports

Published: June 14, 2023

Wing Interferential Patterns (WIPs) and machine learning, a step toward automatized tsetse (Glossina spp.) identification.

Wing Interferential Patterns (WIPs) and machine learning, a step toward automatized tsetse (Glossina spp.) identification.

Journal: Scientific reports

Published: October 06, 2022

Evaluation by a Machine Learning System of Two Preparations for Small Bowel Capsule Endoscopy: The BUBS (Burst Unpleasant Bubbles with Simethicone) Study.

Evaluation by a Machine Learning System of Two Preparations for Small Bowel Capsule Endoscopy: The BUBS (Burst Unpleasant Bubbles with Simethicone) Study.

Journal: Journal of clinical medicine

Published: April 20, 2022

A multisystem-compatible deep learning-based algorithm for detection and characterization of angiectasias in small-bowel capsule endoscopy. A proof-of-concept study.

A multisystem-compatible deep learning-based algorithm for detection and characterization of angiectasias in small-bowel capsule endoscopy. A proof-of-concept study.

Journal: Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver

Published: June 24, 2021

A neural network-based algorithm for assessing the cleanliness of small bowel during capsule endoscopy.

A neural network-based algorithm for assessing the cleanliness of small bowel during capsule endoscopy.

Journal: Endoscopy

Published: October 30, 2020

Showing 1-10 of 10

Last Updated: 09/26/2026