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Fast learning-based registration of sparse 3D clinical images

• Authors : Lewis, Kathleen M.(Kathleen Marie); Guttag, John V; Dalca, Adrian Vasile ...

• Source: arXiv

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Fast learning-based registration of sparse 3D clinical images

• Authors : Lewis, Kathleen; Rost, Natalia S.; Guttag, John ...

• Source: Proceedings of the ACM Conference on Health, Inference, and Learning

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Analyse de l'encodeur pour la segmentation d'une base de données hétérogène de photographies de plaies chroniques avec peu d'annotations

• Authors : Picaud, Guillaume; Chaumont, Marc; Subsol, Gérard ...

Subjects: Images cliniques Self supervised learning; Weight initialization; Clinical imagesLa Rochelle; France

• Source: CNIA 2024 - 8e Conférence Nationale en Intelligence Artificielle ; https://hal.science/hal-04628579 ; CNIA 2024 - 8e Conférence Nationale en Intelligence Artificielle, PFIA, Jul 2024, La Rochelle,

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Design of a System for Melanoma Detection Through the Processing of Clinical Images Using Artificial Neural Networks

• Authors : Mahecha, Marco; Parra, Octavio; Velandia, Julio ...

Subjects: Neural networks; Deep learning; Clinical diagnosisKuwait City; Kuwait

• Source: Lecture Notes in Computer Science ; 17th Conference on e-Business, e-Services and e-Society (I3E) ; https://hal.inria.fr/hal-02274187 ; 17th Conference on e-Business, e-Services and e-Society (I3E),

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Actes de la 27e Conférence Nationale en Intelligence Artificielle ; Actes de la 27e Conférence Nationale en Intelligence Artificielle: CNIA 2024

• Authors : Aussenac-Gilles, Nathalie;

Subjects: Apprentissage automatique Réseaux adversoriels génératifs StyleGAN2 Meiofauna Apprentissage auto-supervisé segmentation Dinov2 images cliniques Self supervised learning segmentation Dinov2 weight initialization clinical images Apprentissage actif design expérimental flou règles optimisation Active learning experimental design fuzzy rules optimization interpretability Yolov8 Détection d'objets en peu d'exemples Apprentissage Yolov8 Few-Shot Object-Detection Transfer Learning Health data Epidemiology Philosophy of technology FAI-Rification AI ethics Trust AI based System decision support system Human Machine Teaming Analyse de l'apprentissage apprentissage supervisé Moodle sur-échantillonnage Learning analytics Moodle Oversampling Supervised learning Digital maps OCR clustering Neurosymbolique classification logique Neurosymbolic classification logic; Apprentissage automatique; Réseaux adversoriels génératifs

• Source: Plate-Forme Intelligence Artificielle ; https://hal.science/hal-04627586 ; Plate-Forme Intelligence Artificielle, Association Française pour l'Intelligence Artificielle, 2024

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Learning to look - Purpose and design of an awareness-raising online course in veterinary sciences

• Authors : Tasnier, Sophie; Busoni, Valeria; Hanzen, Christian

Subjects: awareness; veterinary sciences; observation

• Source: Proceedings of the 5th Workshop on Awareness and Reflection in Technology-Enhanced Learning, 35-42 (2015-09-15); 5th Workshop on Awareness and Reflection in Technology-Enhanced Learning (ARTEL),

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Lesion characterization using spectral mammography

• Authors : Norell, Björn; Fredenberg, Erik; Leifland, Karin

Subjects: cyst; lesion; mammography

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Learning to look - Purpose and design of an awareness-raising online course in veterinary sciences ; Savoir voir - Intention et design pédagogiques d'un cours en ligne d'entrainement aux capacités visuelles en sciences vétérinaires

• Authors : Tasnier, Sophie; Busoni, Valeria; Hanzen, Christian

Subjects: awareness; veterinary sciences; observation

• Source: Proceedings of the 5th Workshop on Awareness and Reflection in Technology-Enhanced Learning, 35-42 (2015-09-15); 5th Workshop on Awareness and Reflection in Technology-Enhanced Learning (ARTEL),

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Race- and Ethnicity-Stratified Analysis of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners.

• Authors : Jain, Ayush¹; Way, David¹; Gupta, Vishakha¹

• Source: iProceedings. 2022, Vol. 8 Issue 1, p1-2. 2p.

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Nodules Segmentation in Breast Ultrasound using the Artificial Neural Network Self-Organizing Map.

• Authors : Marcomini, Karem Daiane¹ ; Schiabel, Homero¹

• Source: Proceedings of the World Congress on Engineering 2012 Volume II. 2012, p1-4. 4p.

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