Learning grayscale mathematical morphology with smooth morphological layers
The integration of mathematical morphology operations within convolutional neural network
architectures has received an increasing attention lately. However, replacing standard …
architectures has received an increasing attention lately. However, replacing standard …
Deep morphological neural networks
Mathematical morphology intends to extract object features such as geometric and
topological structures in digital images. Given a set of target images and original images, it is …
topological structures in digital images. Given a set of target images and original images, it is …
Going beyond p-convolutions to learn grayscale morphological operators
A Kirszenberg, G Tochon, É Puybareau… - … Conference on Discrete …, 2021 - Springer
Integrating mathematical morphology operations within deep neural networks has been
subject to increasing attention lately. However, replacing standard convolution layers with …
subject to increasing attention lately. However, replacing standard convolution layers with …
Topological similarity index and loss function for blood vessel segmentation
RJ Araújo, JS Cardoso, HP Oliveira - arxiv preprint arxiv:2107.14531, 2021 - arxiv.org
Blood vessel segmentation is one of the most studied topics in computer vision, due to its
relevance in daily clinical practice. Despite the evolution the field has been facing …
relevance in daily clinical practice. Despite the evolution the field has been facing …
On some associations between mathematical morphology and artificial intelligence
This paper aims at providing an overview of the use of mathematical morphology, in its
algebraic setting, in several fields of artificial intelligence (AI). Three domains of AI will be …
algebraic setting, in several fields of artificial intelligence (AI). Three domains of AI will be …
Semiring Activation in Neural Networks
B Smets, PD Donker, JW Portegies, R Duits - arxiv preprint arxiv …, 2024 - arxiv.org
We introduce a class of trainable nonlinear operators based on semirings that are suitable
for use in neural networks. These operators generalize the traditional alternation of linear …
for use in neural networks. These operators generalize the traditional alternation of linear …
Classification of chest X-ray images using novel adaptive morphological neural networks
The chest X-ray images are difficult to classify for the radiologists due to the noisy nature.
The existing models based on convolutional neural networks contain a giant number of …
The existing models based on convolutional neural networks contain a giant number of …
A novel multi-pattern solder joint simultaneous segmentation algorithm for PCB selective packaging systems
L Huang, S Shen, F **e, J Zhao, J Han… - International Journal of …, 2019 - World Scientific
To prevent any negative electromagnetic influence of high-density integrated circuits, an
insulation package needs to be specially designed to shield it. Aiming at the low efficiency …
insulation package needs to be specially designed to shield it. Aiming at the low efficiency …
Texture-based image transformations for improved deep learning classification
In this paper, we examine the effect of texture-based image transformation on classification
performance. A novel combination of mathematical morphology operations and contrast …
performance. A novel combination of mathematical morphology operations and contrast …
Morphological network: Network with morphological neurons
R Mondal - 2021 - search.proquest.com
Image processing with traditional approaches mainly use the tools of linear systems.
However, linear approaches are not well suited and may even fail to solve problems …
However, linear approaches are not well suited and may even fail to solve problems …