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Predicting recurrence of prostate cancer after radical treatment using AI models based on PET/CT radiomics: a dual-center study. [PDF]

Front Oncol
Yi Z, Li W, Lou Y, Zhou Q.
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On decomposing MLPs

IEEE International Conference on Neural Networks, 2002
The benefits of decomposing the multilayer preceptron (MLP) for pattern recognition tasks are investigated. For the case of N classes, instead of using 1 MLP with N outputs, N MLPs, each with a single output are used. In practice, this allows the use of fewer hidden units than would be used in the single MLP. It is found that decomposing the problem in
Simon M. Lucas, Z. Zhao, G. Cawley, P. Noakes   +3 more
openaire   +1 more source

MS-MLP: Multi-scale Sampling MLP for ECG Classification

2022 30th European Signal Processing Conference (EUSIPCO), 2022
Transformer-based models (i.e., Fusing-TF and LDTF) have achieved state-of-the-art performance for electrocardiogram (ECG) classification. However, these models may suffer from low training efficiency due to the high model complexity associated with the attention mechanism.
Wang, Wenbo, Guan, Jian, Che, Xinyi, Wang, Wenwu   +3 more
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MLP bilinear separation

Neural Computing and Applications, 2009
In this paper, we present a thorough mathematical analysis of the use of neural networks to solve a specific classification problem consisting of a bilinear boundary. The network under consideration is a three-layered perceptron with two hidden neurons having the sigmoid serving as the activation function.
Richard Labib, Karim Khattar
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Neighbour-based MLPs

Proceedings of ICNN'95 - International Conference on Neural Networks, 2002
This paper reviews a Bayesian approach to classifying multi-spectral image data where the pixel labels are assumed to be spatially correlated. A Markov random field (MRF) model is introduced to model localized dependence, so that a label is assumed to be conditional on the labels of the neighbouring pixels only.
Rob A. Dunne, N. A. Campbell
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Inception MLP: A vision MLP backbone for multi-scale feature extraction

Information Sciences
Xixin Cao
exaly   +2 more sources

Limitation of connectionism in MLP

1993
In this work we study the behavior of restricted connectionism schemes aimed at solving one of the problems found in the implementation of Artificial Neural Networks (ANNs) in VLSI technology. We limit our study to the classical backpropagation trained MLPs and we discuss the limitations of restricted connectionism by means of a simulation of two tasks
Carlos Vázquez Regueiro, Senén Barro, A. Yáñez   +2 more
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Data Fusion Using an MLP

Procedings of the British Machine Vision Conference 1991, 1991
A binary classification problem is solved by acting on the combined evidence of several early vision modules. Each module gives an opinion as to the identity of an individual image element, and a consensus is reached by a trained Multi-Layer Perceptron (MLP).
David M. Booth, Neil A. Thacker, John E. W. Mayhew, Michael Pidcock   +3 more
openaire   +1 more source