A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting

Ullah S, Amanullah A, Roy K, Lee J-A, Chul-Jun S, Jungeblut T (2023)
In: International Conference on Computer Vision (ICCV) 2023. Paris France .

Kurzbeitrag Konferenz / Poster | Veröffentlicht | Englisch
 
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Autor*in
Ullah, SanaUniBi ; Amanullah, Amanullah; Roy, Kaushik; Lee, Jeong-A; Chul-Jun, Son; Jungeblut, ThorstenUniBi
Abstract / Bemerkung

This paper presents a hybrid SC-NN architecture for effective image inpainting, combining SNNs and CNNs. The model, which includes SNNConv2d layers, outperforms
state-of-the-art approaches by decreasing reconstruction mistakes with lower loss values. The effectiveness indicates a wide range of applications in image regeneration assignments. Combining SNNConv2d with regular CNN layers takes advantage of both SNN and CNN strengths. Future plans include refining the model, investigating applications, and solving real-world problems. The findings highlight SNN’s potential for enhancing artificial intelligence.

Erscheinungsjahr
2023
Titel des Konferenzbandes
International Conference on Computer Vision (ICCV) 2023
Konferenz
International Conference on Computer Vision (ICCV) 2023
Konferenzort
Paris France
Konferenzdatum
2023-10-2 – 2023-10-6
Page URI
https://pub.uni-bielefeld.de/record/2985712

Zitieren

Ullah S, Amanullah A, Roy K, Lee J-A, Chul-Jun S, Jungeblut T. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. In: International Conference on Computer Vision (ICCV) 2023. Paris France ; 2023.
Ullah, S., Amanullah, A., Roy, K., Lee, J. - A., Chul-Jun, S., & Jungeblut, T. (2023). A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. International Conference on Computer Vision (ICCV) 2023 Paris France . https://doi.org/10.5281/zenodo.10458019
Ullah, Sana, Amanullah, Amanullah, Roy, Kaushik, Lee, Jeong-A, Chul-Jun, Son, and Jungeblut, Thorsten. 2023. “A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting”. In International Conference on Computer Vision (ICCV) 2023. Paris France .
Ullah, S., Amanullah, A., Roy, K., Lee, J. - A., Chul-Jun, S., and Jungeblut, T. (2023). “A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting” in International Conference on Computer Vision (ICCV) 2023 (Paris France ).
Ullah, S., et al., 2023. A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. In International Conference on Computer Vision (ICCV) 2023. Paris France .
S. Ullah, et al., “A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting”, International Conference on Computer Vision (ICCV) 2023, Paris France : 2023.
Ullah, S., Amanullah, A., Roy, K., Lee, J.-A., Chul-Jun, S., Jungeblut, T.: A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting. International Conference on Computer Vision (ICCV) 2023. Paris France (2023).
Ullah, Sana, Amanullah, Amanullah, Roy, Kaushik, Lee, Jeong-A, Chul-Jun, Son, and Jungeblut, Thorsten. “A Hybrid Spiking-Convolutional Neural Network Approach for Advancing High-Quality Image Inpainting”. International Conference on Computer Vision (ICCV) 2023. Paris France , 2023.
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