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GRUU-Net: Integrated convolutional and gated recurrent neural network for cell segmentation
Medical Image Analysis, 2019Cell segmentation in microscopy images is a common and challenging task. In recent years, deep neural networks achieved remarkable improvements in the field of computer vision. The dominant paradigm in segmentation is using convolutional neural networks, less common are recurrent neural networks.
Thomas Wollmann +5 more
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Computer Simulations of Recurrent Neural Nets for Temporal Recognition Problems
1992A number of approaches are presented to the use of neural nets with feedback to handle the recognition of temporal data and these are assessed with respect to resilience (ability to handle noisy or incomplete input) and performance in handling similar and overlapping patterns.
G. S. Cooper, T. M. Child
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Alpha-nets: A recurrent ‘neural’ network architecture with a hidden Markov model interpretation
Speech Communication, 1990Abstract A hidden Markov model isolated word recogniser using full likelihood scoring for each word model can be treated as a recurrent ‘neural’ network. The units in the recurrent loop are linear, but the observations enter the loop via a multiplication.
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Fast convergence algorithm for multilayer and recurrent neural nets
1998The presentation deals with a class of fast algoritms for training feedforward and recurrent neural networks, especially suited dor signal processing and telecommunications.
DI CLAUDIO, Elio +2 more
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Recurrent neural nets as building blocks for human word recognition
2nd European Conference on Speech Communication and Technology (Eurospeech 1991), 1991Peter Wittenburg, R. Couwenberg
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DRC-NET: Densely Connected Recurrent Convolutional Neural Network for Speech Dereverberation
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Jinjiang Liu, Xueliang Zhang 0001
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The Treatment of Recurrent or Metastatic Breast Cancer
Ca-A Cancer Journal for Clinicians, 1963R N Grant
exaly

