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Jingyi Hu, Junfeng Guo, Zhiyuan Rui and Zhiming Wang
To solve the problem that noise seriously affects the online monitoring of parts signals of outdoor machinery, this paper proposes a signal reconstruction method integrating deep neural network and compression sensing, called ADMM-1DNet, and gives a deta...
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Steven Guan, Ko-Tsung Hsu and Parag V. Chitnis
Simulation tools for photoacoustic wave propagation have played a key role in advancing photoacoustic imaging by providing quantitative and qualitative insights into parameters affecting image quality. Classical methods for numerically solving the photoa...
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Yuxing Wang, Nan Liu, Zhiwen Pan and Xiaohu You
Network slicing is a key technology for 5G networks, which divides the traditional physical network into multiple independent logical networks to meet the diverse requirements of end-users. This paper focuses on the resource allocation problem in the sce...
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Nika Nizharadze, Arash Farokhi Soofi and Saeed Manshadi
Predicting the price gap between the day-ahead Market (DAM) and the real-time Market (RTM) plays a vital role in the convergence bidding mechanism of Independent System Operators (ISOs) in wholesale electricity markets. This paper presents a model to pre...
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Christian Moya and Guang Lin
The Deep Operator Network (DeepONet) framework is a different class of neural network architecture that one trains to learn nonlinear operators, i.e., mappings between infinite-dimensional spaces. Traditionally, DeepONets are trained using a centralized ...
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Sergey A. Soldatov, Danil M. Pashkov, Sergey A. Guda, Nikolay S. Karnaukhov, Alexander A. Guda and Alexander V. Soldatov
Microscopic tissue analysis is the key diagnostic method needed for disease identification and choosing the best treatment regimen. According to the Global Cancer Observatory, approximately two million people are diagnosed with colorectal cancer each yea...
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Chun Liu, Yaohui Hu, Zheng Li, Junkui Xu, Zhigang Han and Jianzhong Guo
The classification and recognition of the shapes of buildings in map space play an important role in spatial cognition, cartographic generalization, and map updating. As buildings in map space are often represented as the vector data, research was conduc...
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Dan Malowany and Hugo Guterman
Computer vision is currently one of the most exciting and rapidly evolving fields of science, which affects numerous industries. Research and development breakthroughs, mainly in the field of convolutional neural networks (CNNs), opened the way to unprec...
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Francesca Condorelli, Fulvio Rinaudo, Francesco Salvadore and Stefano Tagliaventi
Documenting Cultural Heritage through the extraction of 3D measures with photogrammetry is fundamental for the conservation of the memory of the past. However, when the heritage has been lost the only way to recover this information is the use of histori...
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Yu Feng, Frank Thiemann and Monika Sester
Cartographic generalization is a problem, which poses interesting challenges to automation. Whereas plenty of algorithms have been developed for the different sub-problems of generalization (e.g., simplification, displacement, aggregation), there are sti...
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