Dec 19, 2019 · In this work, we design a neural network named MCRNN for classifying signals with slight distinction. This model combines advantages of both ...
Dec 21, 2019 · ABSTRACT. In this work, we design a neural network named MCRNN for classifying signals with slight distinction. This model combines.
In this work, we design a neural network named MCRNN for classifying signals with slight distinction. This model combines advantages of both Convolutional ...
May 28, 2024 · This paper presents the results of the investigations of a cohort of 26 students exposed to Guided Imagery relaxation technique and mental task workloads.
May 5, 2023 · In this paper we focus on the development of a convolutional recurrent neural network (CRNN) to categorize biosignals collected in the Hellenic Trench.
Missing: Mixed | Show results with:Mixed
Convolutional recurrent neural networks for music classification. Abstract: We introduce a convolutional recurrent neural network (CRNN) for music tagging.
Missing: Mixed learning
Publication Results. Mixed convolutional recurrent neural networks : learning for signal classification. Publication type: Conference Proceeding.
This work has explored the neuro-evolution application to the automatic design of convolutional neural networks topologies and also has devised a novel solution ...
Jun 22, 2023 · We proposed a deep learning model powered up by state-of-the-art methods to classify responders (R) and non-responders (NR) to rTMS treatment.
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We propose a model that enhances this fea- ture extraction process for the case of sequential data, by feeding patches of the data into a recurrent neural ...