ENHANCING IMAGE RECOGNITION PATTERNS WITH HOPFIELD NEURAL NETWORKS

Taras Batiuk

doi:10.36074/logos-14.02.2025.041

Інформаційні технології та системи

February 14, 2025; Boston, USA: VII Міжнародна науково-практична конференція «SCIENTIFIC PRACTICE: MODERN AND CLASSICAL RESEARCH METHODS»

ENHANCING IMAGE RECOGNITION PATTERNS WITH HOPFIELD NEURAL NETWORKS

Taras Batiuk ⁺⁻

DOI: https://doi.org/10.36074/logos-14.02.2025.041
Опубліковано: 14.03.2025

Анотація

In 1982, John Hopfield introduced his associative network during a presentation at the National Academy of Sciences. To pay homage to Hopfield and this innovative modeling approach, this network paradigm is commonly known as the Hopfield network. This network concept draws inspiration from the principles of dynamic systems in physics. Initially, it found applications in associative memory and problem optimization.

Посилання

Corti L., Zanetti M., Tricella G., Bonati M. Social media analysis of Twitter tweets related to ASD in 2019–2020, with particular attention to COVID-19: topic modelling and sentiment analysis. Journal of Big Data. 2022. № 9 (1). P. 1–17.
Liu H. Online review analysis on various networks’ consumer feedback using deep learning. IET networks. 2022. № 11 (6). P. 234–244.
Wang Y., Chen Z., Fu C. Synergy Masks of Domain Attribute Model DaBERT: Emotional Tracking on Time-Varying Virtual Space Communication. Sensors. 2022. № 22 (21). P. 450–471.
Wang Y., Guo J., Yuan C., Li B. Sentiment Analysis of Twitter Data. Applied Sciences. 2022. № 12 (8). P. 157–189.
Albahli S., Irtaza A., Nazir T., Mehmood A., Ali A., Waleed Albattah W. A Machine Learning Method for Prediction of Stock Market Using Real-Time Twitter Data. Electronics. 2022. № 11 (20). P. 341–363.

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Як цитувати

Batiuk , T. (2025). ENHANCING IMAGE RECOGNITION PATTERNS WITH HOPFIELD NEURAL NETWORKS. Збірник наукових праць «ΛΌГOΣ», (February 14, 2025; Boston, USA), 194–198. https://doi.org/10.36074/logos-14.02.2025.041

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Статті цього автора (авторів), які найбільше читають

[1] Corti L., Zanetti M., Tricella G., Bonati M. Social media analysis of Twitter tweets related to ASD in 2019–2020, with particular attention to COVID-19: topic modelling and sentiment analysis. Journal of Big Data. 2022. № 9 (1). P. 1–17.

[2] Liu H. Online review analysis on various networks’ consumer feedback using deep learning. IET networks. 2022. № 11 (6). P. 234–244.

[3] Wang Y., Chen Z., Fu C. Synergy Masks of Domain Attribute Model DaBERT: Emotional Tracking on Time-Varying Virtual Space Communication. Sensors. 2022. № 22 (21). P. 450–471.

[4] Wang Y., Guo J., Yuan C., Li B. Sentiment Analysis of Twitter Data. Applied Sciences. 2022. № 12 (8). P. 157–189.

[5] Albahli S., Irtaza A., Nazir T., Mehmood A., Ali A., Waleed Albattah W. A Machine Learning Method for Prediction of Stock Market Using Real-Time Twitter Data. Electronics. 2022. № 11 (20). P. 341–363.