Zobrazeno 1 - 10
of 532
pro vyhledávání: '"Data encoding"'
Autor:
Antonio Tudisco, Deborah Volpe, Giacomo Ranieri, Gianbiagio Curato, Davide Ricossa, Mariagrazia Graziano, Davide Corbelletto
Publikováno v:
IEEE Access, Vol 12, Pp 102918-102940 (2024)
Home banking and digital payments diffusion has greatly increased in recent years. As a result, fraud has also dramatically grown, resulting in the loss of billions of dollars worldwide every year. Therefore, banks and financial institutions are requ
Externí odkaz:
https://doaj.org/article/b0cae32328bc4049ad2f549ad25dcb69
Autor:
Deepak Ranga, Aryan Rana, Sunil Prajapat, Pankaj Kumar, Kranti Kumar, Athanasios V. Vasilakos
Publikováno v:
Mathematics, Vol 12, Iss 21, p 3318 (2024)
Quantum computing and machine learning (ML) have received significant developments which have set the stage for the next frontier of creative work and usefulness. This paper aims at reviewing various data-encoding techniques in Quantum Machine Learni
Externí odkaz:
https://doaj.org/article/20b94082377442869c2702ce6b7d16d3
Autor:
Jianing Chen, Yan Li
Publikováno v:
Frontiers in Quantum Science and Technology, Vol 3 (2024)
The evolution of quantum computers has encouraged research into how to handle tasks with significant computation demands in the past few years. Due to the unique advantages of quantum parallelism and entanglement, various types of quantum machine lea
Externí odkaz:
https://doaj.org/article/23ebf8e53fcb42328085a0b98c5bbca3
Publikováno v:
Exploratory Research in Clinical and Social Pharmacy, Vol 14, Iss , Pp 100463- (2024)
Background: Machine learning (ML) prediction models in healthcare and pharmacy-related research face challenges with encoding high-dimensional Healthcare Coding Systems (HCSs) such as ICD, ATC, and DRG codes, given the trade-off between reducing mode
Externí odkaz:
https://doaj.org/article/29d4069d9d5440419938959fcb08bd34
Publikováno v:
Frontiers in Physics, Vol 12 (2024)
Quantum Convolutional Neural Network (QCNN) has achieved significant success in solving various complex problems, such as quantum many-body physics and image recognition. In comparison to the classical Convolutional Neural Network (CNN) model, the QC
Externí odkaz:
https://doaj.org/article/d01dcdb0cea147b5a79e3ca38d375b17
Publikováno v:
Gong-kuang zidonghua, Vol 50, Iss 1, Pp 17-24, 34 (2024)
In current coal mine data acquisition, fusion, and sharing, there are problems of lack of standardization and semantic inconsistency in device attributes, inability to cross operating systems in data acquisition protocols, poor real-time data access,
Externí odkaz:
https://doaj.org/article/8a452c6bd2cd4e3fb3fe6e93975946c1
Publikováno v:
IEEE Access, Vol 11, Pp 120654-120665 (2023)
Spiking Neural Networks (SNNs) are promising candidates for low-power and low-latency embedded artificial intelligence. However, those networks require event-based data produced by neuromorphic sensors which are not widely available, except for a few
Externí odkaz:
https://doaj.org/article/0de104579a714d9581c7c8d5c4c6fc0b
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 1, p 015048 (2024)
There have been numerous quantum neural networks reported, but they struggle to match traditional neural networks in accuracy. Given the huge improvement of the neural network models’ accuracy by two-dimensional tensor network (TN) states in classi
Externí odkaz:
https://doaj.org/article/f999f6fd687b443095ca2b84225931de
Publikováno v:
E3S Web of Conferences, Vol 477, p 00074 (2024)
The utilization of neural model techniques for predicting learner performance has exhibited success across various technical domains, including natural language processing. In recent times, researchers have progressively directed their attention towa
Externí odkaz:
https://doaj.org/article/d21c22b8f9d04752b8a7763fcf5adbba
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