X-ray micro-tomography to quantify frozen ice cream structure, 24ième Congrès International du Froid ICR 2015, p.8, 2015. ,
URL : https://hal.archives-ouvertes.fr/hal-01523639
Segnet: A deep convolutional encoder-decoder architecture for image segmentation, IEEE transactions on pattern analysis and machine intelligence, vol.39, pp.2481-2495, 2017. ,
Semi-supervised deep learning for fully convolutional networks, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.311-319, 2017. ,
What's the point: Semantic segmentation with point supervision, European conference on computer vision, pp.549-565, 2016. ,
Multitask learning for segmentation of building footprints with deep neural networks, 2017. ,
Geodesic active contours, International journal of computer vision, vol.22, pp.61-79, 1997. ,
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs, IEEE transactions on pattern analysis and machine intelligence, vol.40, pp.834-848, 2018. ,
Semantic image segmentation with deep convolutional nets and fully connected crfs, 2014. ,
A comparative study of desktop-and synchrotron radiation-based X-ray microtomography analysing air bubbles and ice crystals in ice cream ,
Imagenet: A largescale hierarchical image database, 2009 IEEE conference on computer vision and pattern recognition, pp.248-255, 2009. ,
The pascal visual object classes challenge: A retrospective, International journal of computer vision, vol.111, pp.98-136, 2015. ,
Coarse-to-fine volumetric segmentation of teeth in Cone-Beam CT, 2018. ,
Stacked U-Nets for Ground Material Segmentation in Remote Sensing Imagery, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.257-261, 2018. ,
Multiclass weighted loss for instance segmentation of cluttered cells, 25th IEEE International Conference on Image Processing (ICIP), pp.2451-2455, 2018. ,
Revealing the microstructural stability of a three-phase soft solid (ice cream) by 4D synchrotron X-ray tomography, Journal of food engineering, vol.237, pp.204-214, 2018. ,
Synchrotron X-ray tomographic quantification of microstructural evolution in ice cream-a multi-phase soft solid, Rsc Advances, vol.7, pp.15561-15573, 2017. ,
Weaklysupervised semantic segmentation network with deep seeded region growing, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.7014-7023, 2018. ,
Batch normalization: Accelerating deep network training by reducing internal covariate shift, 2015. ,
Coarse-to-fine Semantic Segmentation from Image-level Labels, 2018. ,
Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.7482-7491, 2018. ,
Simple does it: Weakly supervised instance and semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.876-885, 2017. ,
Adam: A method for stochastic optimization, 2014. ,
Seed, expand and constrain: Three principles for weakly-supervised image segmentation, European Conference on Computer Vision, pp.695-711, 2016. ,
FickleNet: Weakly and Semi-supervised Semantic Image Segmentation using Stochastic Inference, 2019. ,
Scribblesup: Scribble-supervised convolutional networks for semantic segmentation, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.3159-3167, 2016. ,
A survey on deep learning in medical image analysis, Medical image analysis, vol.42, pp.60-88, 2017. ,
Fully convolutional networks for semantic segmentation, Proceedings of the IEEE conference on computer vision and pattern recognition, pp.3431-3440, 2015. ,
Deep Learning with Mixed Supervision for Brain Tumor Segmentation, 2018. ,
URL : https://hal.archives-ouvertes.fr/hal-01952458
Weakly-and semi-supervised learning of a deep convolutional network for semantic image segmentation, Proceedings of the IEEE international conference on computer vision, pp.1742-1750, 2015. ,
Deep semi-supervised segmentation with weightaveraged consistency targets, Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, pp.12-19, 2018. ,
3D-characterization of three-phase systems using X-ray tomography: tracking the microstructural evolution in ice cream, Soft Matter, vol.8, pp.4584-4594, 2012. ,
A Multitask Learning Architecture for Simultaneous Segmentation of Bright and Red Lesions in Fundus Images, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.101-108, 2018. ,
A novel weakly supervised Multitask Architecture for Retinal Lesions Segmentation on Fundus Images, IEEE transactions on medical imaging, 2019. ,
U-net: Convolutional networks for biomedical image segmentation, International Conference on Medical image computing and computer-assisted intervention, pp.234-241, 2015. ,
Grabcut: Interactive foreground extraction using iterated graph cuts, ACM transactions on graphics (TOG), vol.23, pp.309-314, 2004. ,
An overview of multi-task learning in deep neural networks, 2017. ,
MS-Net: Mixed-supervision fullyconvolutional networks for full-resolution segmentation, International Conference on Medical Image Computing and Computer-Assisted Intervention, pp.379-387, 2018. ,
Joint weakly and semi-supervised deep learning for localization and classification of masses in breast ultrasound images, IEEE transactions on medical imaging, vol.38, pp.762-774, 2019. ,
Saliency guided deep network for weakly-supervised image segmentation, Pattern Recognition Letters, vol.120, pp.62-68, 2019. ,
Stacked u-nets with multi-output for road extraction, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp.187-1874, 2018. ,
Minimizing Supervision for Free-space Segmentation, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp.988-997, 2018. ,
A two-stage 3D Unet framework for multi-class segmentation on full resolution image, 2018. ,
Repulsion loss: Detecting pedestrians in a crowd, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.7774-7783, 2018. ,
Revisiting dilated convolution: A simple approach for weakly-and semi-supervised semantic segmentation, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.7268-7277, 2018. ,
Stc: A simple to complex framework for weakly-supervised semantic segmentation, IEEE transactions on pattern analysis and machine intelligence, vol.39, pp.2314-2320, 2017. ,
, Conditional random fields as recurrent neural networks". In: Proceedings of the IEEE international conference on computer vision, pp.1529-1537, 2015.
Weakly supervised 3D deep learning for breast cancer classification and localization of the lesions in MR images, Journal of Magnetic Resonance Imaging, 2019. ,