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Neural networks literature review

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A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. Neural networks can adapt to changing input; so the network generates the best possible result without needing to redesign the output criteria. The concept of neural networks, which has its roots in artificial intelligence , is swiftly gaining popularity in the development of trading systems. The network bears a strong resemblance to statistical methods such as curve fitting and regression analysis. A neural network contains layers of interconnected nodes.
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Robustness and Repeatability of modern Deep Neural Networks: a review

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Neural network-based approaches for biomedical relation classification: A review

Nowadays, Deep Neural Networks are among the main tools used in various sciences. Convolutional Neural Network is a special type of DNN consisting of several convolution layers, each followed by an activation function and a pooling layer. The pooling layer is an important layer that executes the down-sampling on the feature maps coming from the previous layer and produces new feature maps with a condensed resolution. This layer drastically reduces the spatial dimension of input. It serves two main purposes. The first is to reduce the number of parameters or weights, thus lessening the computational cost. The second is to control the overfitting of the network.
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Neural network-based approaches for biomedical relation classification: A review

Skip to Main Content. A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. Use of this web site signifies your agreement to the terms and conditions. Literature review of artificial neural networks and knowledge-based systems for image analysis and interpretation of data in remote sensing Abstract: Remote sensing is a scientific discipline involved in the study and management of the environment and natural resources. Current developments in data acquisition and the diversity of sensors generate great amounts of data.
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You should first give a background literature review on the topic of the dataset, you should then provide a design of the neural network used including justifications of design choices. You should comment on how well the network performed and cite the performance data such as the classification accuracy, confusion matrixes and performance under noise. Background literature review Your background literature review should explain the topic of choice and explore the problem in detail. The literature review should explain the input values, the classifications and any other important information about the problem. You should also consider if any other research has attempted to solve this problem before and compare your results with those.
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