نتایج جستجو برای: long learning
تعداد نتایج: 1342432 فیلتر نتایج به سال:
Introduction: There are evidences showing the role of nitric oxide in the opiate reward properties. The role of nitric oxide signaling pathway as an intracellular mechanism on augmentation of long term potentiation in hippocampal CA1 area of rats is also confirmed. It has been also reported that oral morphine dependence facilitates formation of spatial learning and memory via activation of N...
Background and purpose: Aging is associated with brain changes and reduction in motor skill acquisi­tion that can limit its functional capacity. One of the effective interventions is using transcranial direct current stimulation (tDCS). The aim of this systematic review was to assess the effect of tDCS on learning and motor skill in healthy older adults. Materials and methods: A litera...
Asynchronous Advantage Actor- Critic with Adam Optimization and a Layer Normalized Recurrent Network
State-of-the-art deep reinforcement learning models rely on asynchronous training using multiple learner agents and their collective updates to a central neural network. In this thesis, one of the most recent asynchronous policy gradientbased reinforcement learning methods, i.e. asynchronous advantage actor-critic (A3C), will be examined as well as improved using prior research from the machine...
Speech synthesis based on Hidden Markov Models (HMM) and other statistical parametric techniques have been a hot topic for some time. Using this techniques, speech synthesizers are able to produce intelligible and flexible voices. Despite progress, the quality of the voices produced using statistical parametric synthesis has not yet reached the level of the current predominant unit-selection ap...
When processing arguments in online user interactive discourse, it is often necessary to determine their bases of support. In this paper, we describe a supervised approach, based on deep neural networks, for classifying the claims made in online arguments. We conduct experiments using convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) on two claim data sets compile...
Machine learning approaches to source code authorship attribution attempt to find statistical regularities in human-generated source code that can identify the author or authors of that code. This has applications in plagiarism detection, intellectual property infringement, and post-incident forensics in computer security. The introduction of features derived from the Abstract Syntax Tree (AST)...
Relation Join has been applied to generate music harmonic sequences in a given composer or genre style. Compared to other music generation method, Relation Join does not require expert knowledge or estimation of any probabilities while generating a massive number of sequences. However, whether the generated compositions are distinguishable from the original ones is still a question that has not...
Convolutional Neural Network (CNN) models have become the state-of-the-art for most computer vision tasks with natural images. However, these are not best suited for multi-gigapixel resolution Whole Slide Images (WSIs) of histology slides due to large size of these images. Current approaches construct smaller patches from WSIs which results in the loss of contextual information. We propose to c...
We use multilayer Long Short Term Memory (LSTM) networks to learn representations of video sequences. Our model uses an encoder LSTM to map an input sequence into a fixed length representation. This representation is decoded using single or multiple decoder LSTMs to perform different tasks, such as reconstructing the input sequence, or predicting the future sequence. We experiment with two kind...
Automated seizure detection using clinical electroencephalograms is a challenging machine learning problem because the multichannel signal often has an extremely low signal to noise ratio. Events of interest such as seizures are easily confused with signal artifacts (e.g, eye movements) or benign variants (e.g., slowing). Commercially available systems suffer from unacceptably high false alarm ...
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