Model-based inexact graph matching on top of DNNs for semantic scene understanding
Deep learning based pipelines for semantic segmentation often ignore structural information
available on annotated images used for training. We propose a novel post-processing …
available on annotated images used for training. We propose a novel post-processing …
Improving semantic segmentation with graph-based structural knowledge
Deep learning based pipelines for semantic segmentation often ignore structural information
available on annotated images used for training. We propose a novel post-processing …
available on annotated images used for training. We propose a novel post-processing …
Semantic image segmentation based on spatial relationships and inexact graph matching
We propose a method for semantic image segmentation, combining a deep neural network
and spatial relationships between image regions, encoded in a graph representation of the …
and spatial relationships between image regions, encoded in a graph representation of the …
QAP optimisation with reinforcement learning for faster graph matching in sequential semantic image analysis
The paper addresses the fundamental task of semantic image analysis by exploiting
structural information (spatial relationships between image regions). We propose to combine …
structural information (spatial relationships between image regions). We propose to combine …
Reinforcement Learning and Sequential QAP-Based Graph
H Mouchère, R Dahyot - Emerging Topics In Pattern Recognition …, 2024 - books.google.com
This chapter addresses the fundamental task of semantic image analysis by exploiting
structural information (spatial relationships between image regions). We propose to combine …
structural information (spatial relationships between image regions). We propose to combine …
Reinforcement Learning and Sequential QAP-Based Graph Matching for Semantic Segmentation of Images
This chapter addresses the fundamental task of semantic image analysis by exploiting
structural information (spatial relationships between image regions). We propose to combine …
structural information (spatial relationships between image regions). We propose to combine …
Research and implementation of a planimetric measurement technology based on machine vision
Q Zhou, L Zhao, X Bai - International Conference on Signal …, 2023 - spiedigitallibrary.org
To solve the issues with industrial traditional area measurement instruments equipped with
infrared sensors, which are bulky and compute slowly, a planimetric measuring method …
infrared sensors, which are bulky and compute slowly, a planimetric measuring method …
Structural information and (hyper) graph matching for MRI piglet brain extraction
A Durandeau, JB Fasquel, I Bloch, E Mazerand… - 2019 - IET
In the context of the study of the maturation process of the infant brain, this paper focuses on
postnatal piglet brain, whose structure is similar to the one of an infant. Due to the small size …
postnatal piglet brain, whose structure is similar to the one of an infant. Due to the small size …
Apprentissage profond et relations structurelles pour l'analyse d'images: application à l'étude de la lésion cérébrale précoce chez l'enfant après AVC néonatal
P Coupeau - 2023 - theses.hal.science
L'apprentissage profond, notamment en analyse d'images, a connu un essor considérable
ces dernières décennies sans pour autant exploiter la totalité de l'information mise à …
ces dernières décennies sans pour autant exploiter la totalité de l'information mise à …
[PDF][PDF] Méthode d'analyse sémantique d'images combinant apprentissage profond et relations structurelles par appariement de graphes
Résumé Nous proposons une méthode de segmentation sémantique d'images, combinant
apprentissage profond et relations spatiales entre régions. Cette méthode repose sur …
apprentissage profond et relations spatiales entre régions. Cette méthode repose sur …