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18th CAIP 2019: Salerno, Italy - Workshops
- Mario Vento, Gennaro Percannella, Sara Colantonio, Daniela Giorgi, Bogdan J. Matuszewski, Hamideh Kerdegari, Manzoor Razaak:
Computer Analysis of Images and Patterns - CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings. Communications in Computer and Information Science 1089, Springer 2019, ISBN 978-3-030-29929-3
Workshop on Visual Computing and Machine Learning for Biomedical Applications (ViMaBi)
- Valentine Wargnier-Dauchelle, Camille Simon Chane, Aymeric Histace:
Retinal Blood Vessels Segmentation: Improving State-of-the-Art Deep Methods. 5-16 - Liyang Wang, Yu Zhou, Bogdan J. Matuszewski:
A New Hybrid Method for Gland Segmentation in Histology Images. 17-27 - Francesca Lizzi, Francesco Laruina, Piernicola Oliva, Alessandra Retico, Maria Evelina Fantacci:
Residual Convolutional Neural Networks to Automatically Extract Significant Breast Density Features. 28-35 - Benedetta Savelli, Claudio Marrocco, Alessandro Bria, Mario Molinara, Francesco Tortorella:
Combining Convolutional Neural Networks for Multi-context Microcalcification Detection in Mammograms. 36-44 - Abdelbasset Brahim, Mehdi Hajjam El Hassani, Nicolas Farrugia:
Classification of Autism Spectrum Disorder Through the Graph Fourier Transform of fMRI Temporal Signals Projected on Structural Connectome. 45-55 - Cinzia Talamonti, Stefano Piffer, Daniela Greto, Monica Mangoni, Antonio Ciccarone, Paolo Dicarolo, Maria Evelina Fantacci, Franco Fusi, Piernicola Oliva, Letizia Palumbo, Claudio Favre, Lorenzo Livi, Stefania Pallotta, Alessandra Retico:
Radiomic and Dosiomic Profiling of Paediatric Medulloblastoma Tumours Treated with Intensity Modulated Radiation Therapy. 56-64 - Danila Germanese, Sara Colantonio, Claudia Caudai, Maria Antonietta Pascali, Andrea Barucci, Nicola Zoppetti, Simone Agostini, Elena Bertelli, Laura Mercatelli, Vittorio Miele, Roberto Carpi:
May Radiomic Data Predict Prostate Cancer Aggressiveness? 65-75
Workshop on Deep-Learning Based Computer Vision for UAV (DL-UAV)
- Andreas Kamilaris, Corjan van den Brink, Savvas Karatsiolis:
Training Deep Learning Models via Synthetic Data: Application in Unmanned Aerial Vehicles. 81-90 - Moustafa M. Nasralla, Ikram U. Rehman, Drishty Sobnath, Sara Paiva:
Computer Vision and Deep Learning-Enabled UAVs: Proposed Use Cases for Visually Impaired People in a Smart City. 91-99 - Mulham Fawakherji, Ciro Potena, Domenico Daniele Bloisi, Marco Imperoli, Alberto Pretto, Daniele Nardi:
UAV Image Based Crop and Weed Distribution Estimation on Embedded GPU Boards. 100-108 - Manzoor Razaak, Hamideh Kerdegari, Eleanor Davies, Raouf Abozariba, Matthew Broadbent, Katy Mason, Vasileios Argyriou, Paolo Remagnino:
An Integrated Precision Farming Application Based on 5G, UAV and Deep Learning Technologies. 109-119 - Alexander Schelle, Peter Stütz:
Visual Communication with UAV: Use Cases and Achievements. 120-128
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