Blar i forfatter Artikler, rapporter og annet (fysikk og teknologi) "Salberg, Arnt-Børre"
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Deep Semi-Supervised Semantic Segmentation in Multi-Frequency Echosounder Data
Choi, Changkyu; Kampffmeyer, Michael; Jenssen, Robert; Handegard, Nils Olav; Salberg, Arnt-Børre (Journal article; Tidsskriftartikkel; Peer reviewed, 2023-02-01)Multi-frequency echosounder data can provide a broad understanding of the underwater environment in a non-invasive manner. The analysis of echosounder data is, hence, a topic of great importance for the marine ecosystem. Semantic segmentation, a deep learning based analysis method predicting the class attribute of each acoustic intensity, has recently been in the spotlight of the fisheries and aquatic ... -
Explaining decisions of deep neural networks used for fish age prediction
Ordonez, Alba; Eikvil, Line; Salberg, Arnt-Børre; Harbitz, Alf; Murray, Sean Meling; Kampffmeyer, Michael (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-19)Age-reading of fish otoliths (ear stones) is important for the sustainable management of fish resources. However, the procedure is challenging and requires experienced readers to carefully examine annual growth zones. In a recent study, convolutional neural networks (CNNs) have been demonstrated to perform reasonably well on automatically predicting fish age from otolith images. In the present study, ... -
Self-Constructing Graph Convolutional Networks for Semantic Labeling
Liu, Qinghui; Kampffmeyer, Michael; Jenssen, Robert; Salberg, Arnt-Børre (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-02-17)Graph Neural Networks (GNNs) have received increasing attention in many fields. However, due to the lack of prior graphs, their use for semantic labeling has been limited. Here, we propose a novel architecture called the Self-Constructing Graph (SCG), which makes use of learnable latent variables to generate embeddings and to self-construct the underlying graphs directly from the input features ... -
Spectral clustering using PCKID – A probabilistic cluster kernel for incomplete data
Løkse, Sigurd; Bianchi, Filippo Maria; Salberg, Arnt-Børre; Jenssen, Robert (Journal article; Tidsskriftartikkel; Manuskript; Peer reviewed; Preprint, 2017-05-19)In this paper, we propose <i>PCKID</i>, a novel, robust, kernel function for spectral clustering, specifically designed to handle incomplete data. By combining posterior distributions of Gaussian Mixture Models for incomplete data on different scales, we are able to learn a kernel for incomplete data that does not depend on any critical hyperparameters, unlike the commonly used RBF kernel. To evaluate ...