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2On optimizing morphological neural networks for hyperspectral image classification
M. Kukushkin, M. Bogdan, and T. Schmid. Sixteenth International Conference on Machine Vision (ICMV 2023), 13072, page 1307202. International Society for Optics and Photonics, SPIE, (2024)
22 days ago by @scadsfct
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classification
computer
deep
hyperspectral
image
learning
mathematical
morphological
morphology
networks
neuronal
remote
sensing
vision
classificationcomputerdeephyperspectralimagelearningmathematicalmorphologicalmorphologynetworksneuronalremotesensingvision
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2Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries
A. de Carvalho, R. Bonidia, J. Kong, M. Dauhajre, C. Struchiner, G. Goedert, P. Stadler, M. Walter, D. Sanches, T. Day and 9 other author(s). (2024)
a month ago by @scadsfct
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Artificial
Computer
FOS
Intelligence
and
information
sciences
ArtificialComputerFOSIntelligenceandinformationsciences
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2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.
M. Bauer, and C. Augenstein. Proceedings of the 18th Conference on Computer Science and Intelligence Systems, volume 35 of FedCSIS 2023, page 93–101. IEEE, (September 2023)
2 months ago by @scadsfct
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Comparative
Computer
Data
Learning
Self-Supervised
Study
Unlabelled
Vision.
ComparativeComputerDataLearningSelf-SupervisedStudyUnlabelledVision.
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1ArcvaVX: OpenVX Framework for Adaptive Reconfigurable Computer Vision Architectures
L. Kalms, M. Nickel, and D. Göhringer. Applied Reconfigurable Computing. Architectures, Tools, and Applications - 19th International Symposium, ARC 2023, Proceedings, page 97--112. Germany, Springer Science and Business Media B.V., (2023)Publisher Copyright: © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 19th International Symposium on Applied Reconfigurable Computing, ARC 2023 ; Conference date: 27-09-2023 Through 29-09-2023.
2 months ago by @scadsfct
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topic_federatedlearn
Computer
FIS_scads
FPGA,
Framework,
HLS,
OpenVX
Vision,
topic_federatedlearnComputerFIS_scadsFPGA,Framework,HLS,OpenVXVision,
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1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures
N. Charaf, J. Haase, A. Kulisch, {. Elm, and D. Göhringer. 2023 26th Euromicro Conference on Digital System Design (DSD), page 585--592. IEEE, (Sep 8, 2023)Publisher Copyright: © 2023 IEEE.; 26th Euromicro Conference on Digital System Design, DSD 2023 ; Conference date: 06-09-2023 Through 08-09-2023.
2 months ago by @scadsfct
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topic_federatedlearn
Computer
Embedded
FIS_scads
Machine
Runtime,
Scalability,
Shape
algorithms,
architecture,
computing,
learning
vision,
topic_federatedlearnComputerEmbeddedFIS_scadsMachineRuntime,Scalability,Shapealgorithms,architecture,computing,learningvision,
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2On optimizing morphological neural networks for hyperspectral image classification

2Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries

2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.

1ArcvaVX: OpenVX Framework for Adaptive Reconfigurable Computer Vision Architectures

1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures

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publications (hide)11 displayallpublications onlypublications per page5102050100 sort byadded attitleauthorpublication dateentry typehelp for advanced sorting... RSSBibTeXRDFmore...

2On optimizing morphological neural networks for hyperspectral image classification

2Democratising Artificial Intelligence for Pandemic Preparedness and Global Governance in Latin American and Caribbean Countries

2Can Unlabelled Data Improve AI Applications? A Comparative Study on Self-Supervised Learning in Computer Vision.

1ArcvaVX: OpenVX Framework for Adaptive Reconfigurable Computer Vision Architectures

1RTASS: a RunTime Adaptable and Scalable System for Network-on-Chip-Based Architectures

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