Zobrazeno 1 - 10
of 59
pro vyhledávání: '"DECENCIÈRE, ÉTIENNE"'
Publikováno v:
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024, pp. 3447-3458
Point cloud matching, a crucial technique in computer vision, medical and robotics fields, is primarily concerned with finding correspondences between pairs of point clouds or voxels. In some practical scenarios, emphasizing local differences is cruc
Externí odkaz:
http://arxiv.org/abs/2402.17372
Publikováno v:
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), Paris, France, 2023, pp. 4130-4140
When it comes to clinical images, automatic segmentation has a wide variety of applications and a considerable diversity of input domains, such as different types of Magnetic Resonance Images (MRIs) and Computerized Tomography (CT) scans. This hetero
Externí odkaz:
http://arxiv.org/abs/2310.05572
Publikováno v:
2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, 2023
Anomaly detection (AD) in images is a fundamental computer vision problem by deep learning neural network to identify images deviating significantly from normality. The deep features extracted from pretrained models have been proved to be essential f
Externí odkaz:
http://arxiv.org/abs/2307.11197
We propose an incremental improvement to Fully Convolutional Data Description (FCDD), an adaptation of the one-class classification approach from anomaly detection to image anomaly segmentation (a.k.a. anomaly localization). We analyze its original l
Externí odkaz:
http://arxiv.org/abs/2301.09602
Whole slide images (WSI) are microscopy images of stained tissue slides routinely prepared for diagnosis and treatment selection in medical practice. WSI are very large (gigapixel size) and complex (made of up to millions of cells). The current state
Externí odkaz:
http://arxiv.org/abs/2212.03273
Fully Convolutional Data Description (FCDD), an explainable version of the Hypersphere Classifier (HSC), directly addresses image anomaly detection (AD) and pixel-wise AD without any post-hoc explainer methods. The authors claim that FCDD achieves re
Externí odkaz:
http://arxiv.org/abs/2206.02598
Autor:
Basso Della Mea, Guilherme, Ovalle, Cristian, Laiarinandrasana, Lucien, Decencière, Etienne, Dokládal, Petr
Publikováno v:
In Computer Methods in Applied Mechanics and Engineering 1 December 2024 432 Part A
Publikováno v:
Front. Mater., 25 November 2021 Sec. Computational Materials Science
X-ray Computed Tomography (XCT) techniques have evolved to a point that high-resolution data can be acquired so fast that classic segmentation methods are prohibitively cumbersome, demanding automated data pipelines capable of dealing with non-trivia
Externí odkaz:
http://arxiv.org/abs/2107.07468
Akademický článek
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Autor:
Decencière, Etienne, Velasco-Forero, Santiago, Min, Fu, Chen, Juanjuan, Burdin, Hélène, Gauthier, Gervais, Laÿ, Bruno, Bornschloegl, Thomas, Baldeweck, Thérèse
Publikováno v:
Advanced Concepts for Intelligent Vision Systems. ACIVS 2018. Lecture Notes in Computer Science, vol 11182. Springer, Cham
A fully convolutional neural network has a receptive field of limited size and therefore cannot exploit global information, such as topological information. A solution is proposed in this paper to solve this problem, based on pre-processing with a ge
Externí odkaz:
http://arxiv.org/abs/1906.11600