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3D Quantum Cuts for automatic segmentation of porous media in tomography images
(
Elsevier Ltd
, 2022 , Article)
Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves ...
Self-organized Operational Neural Networks with Generative Neurons
(
Elsevier Ltd
, 2021 , Article)
Operational Neural Networks (ONNs) have recently been proposed to address the well-known limitations and drawbacks of conventional Convolutional Neural Networks (CNNs) such as network homogeneity with the sole linear neuron ...
Exploiting heterogeneity in operational neural networks by synaptic plasticity
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
The recently proposed network model, Operational Neural Networks (ONNs), can generalize the conventional Convolutional Neural Networks (CNNs) that are homogenous only with a linear neuron model. As a heterogenous network ...
Operational neural networks
(
Springer
, 2020 , Article)
Feed-forward, fully connected artificial neural networks or the so-called multi-layer perceptrons are well-known universal approximators. However, their learning performance varies significantly depending on the function ...
Progressive Operational Perceptrons with Memory
(
Elsevier B.V.
, 2020 , Article)
Generalized Operational Perceptron (GOP) was proposed to generalize the linear neuron model used in the traditional Multilayer Perceptron (MLP) by mimicking the synaptic connections of biological neurons showing nonlinear ...
Heterogeneous Multilayer Generalized Operational Perceptron
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
The traditional multilayer perceptron (MLP) using a McCulloch-Pitts neuron model is inherently limited to a set of neuronal activities, i.e., linear weighted sum followed by nonlinear thresholding step. Previously, generalized ...
Progressive Operational Perceptrons
(
Elsevier B.V.
, 2017 , Article)
There are well-known limitations and drawbacks on the performance and robustness of the feed-forward, fully-connected Artificial Neural Networks (ANNs), or the so-called Multi-Layer Perceptrons (MLPs). In this study we ...
Human experts vs. machines in taxa recognition
(
Elsevier B.V.
, 2020 , Article)
The step of expert taxa recognition currently slows down the response time of many bioassessments. Shifting to quicker and cheaper state-of-the-art machine learning approaches is still met with expert scepticism towards ...
PyGOP: A Python library for Generalized Operational Perceptron algorithms
(
Elsevier B.V.
, 2019 , Article)
PyGOP provides a reference implementation of existing algorithms using Generalized Operational Perceptron (GOP), a recently proposed artificial neuron model. The implementation adopts a user-friendly interface while allowing ...
Benchmark database for fine-grained image classification of benthic macroinvertebrates
(
Elsevier Ltd
, 2018 , Article)
Managing the water quality of freshwaters is a crucial task worldwide. One of the most used methods to biomonitor water quality is to sample benthic macroinvertebrate communities, in particular to examine the presence and ...