An End to End Encoder-Decoder Network with Multi-scale Feature Pulling for Detecting Local Changes From Video Scene
International audience
Real-time Classification of Aircrafts Manoeuvers
Whether it be in air defense applications or for air traffic control it is highly desirable to be able to assess in real time the type of aircraft one is dealing with. This task may prove useful when the object refuses to cooperate or to confront the transmitted information with the observed trajectory. In the present paper we advocate an approach ...
Can U-Net replace CLV3? Machine learning for the identification of biological landmarks in Shoot Apical Meristem images
Main engine of plant phyllotaxis, the Shoot Apical Meristem (SAM) is a tightly regulated tissue that presents striking spatiotemporal periodicity properties, and due to that, a high level of inter-individual similarity at tissue scale. It is possible to take advantage of this shape similarity to align a population of SAMs imaged using confocal micr...
Revisiting PIN1 polarity interpretation at the SAM based on automated multi-level reconstruction of PIN1 polarities from...
The shoot apical meristem (SAM) produces new aerial organs such as leaves and flowers, patterning the shoot in an arrangement called phyllotaxis. Phyllotaxis is driven by the spatiotemporal dynamics of the auxin hormone at the SAM. It has been shown that auxin accumulation emerges from auxin polar transport, and triggers organ differentiation. In p...
MS-PS: a multi-scale photometric stereo network with a new training database
The photometric stereo (PS) problem consists in reconstructing the 3D-surface of an object, thanks to a set of photographs taken under different lighting directions. In this paper, we propose a multi-scale architecture for PS which, combined with a new dataset, yields state-of-the-art results. Our proposed architecture is flexible: it permits to co...
Satellite Image Processing by Python and R Using Landsat 9 OLI/TIRS and SRTM DEM Data on Côte d’Ivoire, West Africa
In this paper, we propose an advanced scripting approach using Python and R for satellite image processing and modelling terrain in Côte d’Ivoire, West Africa. Data include Landsat 9 OLI/TIRS C2 L1 and the SRTM digital elevation model (DEM). The EarthPy library of Python and ‘raster’ and ‘terra’ packages of R are used as tools for data processing. ...
An Empirical Evaluation of Generative Adversarial Nets in Synthesizing X-ray Chest Images
International audience
A study on loss functions and decision thresholds for the segmentation of multiple sclerosis lesions on spinal cord MRI
Multiple sclerosis (MS) patients often present hyper-intense T2-w lesions in the spinal cord. The severe imbalance between background and lesion classes poses a major challenge to Deep Learning segmentation approaches, requiring for ad hoc strategies. Careful selection of the loss function and adjustment of the conventional 0.5-thresholding may hel...
LEARNING 4DVAR INVERSION DIRECTLY FROM OBSERVATIONS
Variational data assimilation and deep learning share many algorithmic aspects in common. While the former focuses on system state estimation, the latter provides great inductive biases to learn complex relationships. We here design a hybrid architecture learning the assimilation task directly from partial and noisy observations, using the mechanis...
Fixed Point Layers for Geodesic Morphological Operations
Morphological reconstruction is a contour-preserved geodesic transformation that is useful in many fields of image processing. On the other hand, deep learning methods achieved state-of-the-art performance in almost all computer vision tasks. This paper proposes new deep learning layers based on fixed-point morphological reconstruction operations. ...
