AIMC Topic: Neural Networks, Computer

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Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks.

Neural networks : the official journal of the International Neural Network Society
Biological neurons have adaptive nature and perform complex computations involving the filtering of redundant information. However, most common neural cell models, including biologically plausible, such as Hodgkin-Huxley or Izhikevich, do not possess...

On the approximation of functions by tanh neural networks.

Neural networks : the official journal of the International Neural Network Society
We derive bounds on the error, in high-order Sobolev norms, incurred in the approximation of Sobolev-regular as well as analytic functions by neural networks with the hyperbolic tangent activation function. These bounds provide explicit estimates on ...

ABLE: Attention based learning for enzyme classification.

Computational biology and chemistry
Classifying proteins into their respective enzyme class is an interesting question for researchers for a variety of reasons. The open source Protein Data Bank (PDB) contains more than 1,60,000 structures, with more being added everyday. This paper pr...

MGRNN: Structure Generation of Molecules Based on Graph Recurrent Neural Networks.

Molecular informatics
Molecular structure generation is a critical problem for materials science and has attracted growing attention. The problem is challenging since it requires to generate chemically valid molecular structures. Inspired by the recent work in deep genera...

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks.

Sensors (Basel, Switzerland)
A common technique for compressing a neural network is to compute the -rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, is the number of input neurons in the layer, is the...

On the Optimization of Regression-Based Spectral Reconstruction.

Sensors (Basel, Switzerland)
Spectral reconstruction (SR) algorithms attempt to recover hyperspectral information from RGB camera responses. Recently, the most common metric for evaluating the performance of SR algorithms is the Mean Relative Absolute Error (MRAE)-an ℓ1 relative...

Stochastic Memristive Interface for Neural Signal Processing.

Sensors (Basel, Switzerland)
We propose a memristive interface consisting of two FitzHugh-Nagumo electronic neurons connected via a metal-oxide (Au/Zr/ZrO(Y)/TiN/Ti) memristive synaptic device. We create a hardware-software complex based on a commercial data acquisition system, ...

ARMA-Based Segmentation of Human Limb Motion Sequences.

Sensors (Basel, Switzerland)
With the development of human motion capture (MoCap) equipment and motion analysis technologies, MoCap systems have been widely applied in many fields, including biomedicine, computer vision, virtual reality, etc. With the rapid increase in MoCap dat...

Effective Point Cloud Analysis Using Multi-Scale Features.

Sensors (Basel, Switzerland)
Fully exploring the correlation of local features and their spatial distribution in point clouds is essential for feature modeling. This paper, inspired by convolutional neural networks (CNNs), explores the relationship between local patterns and poi...

Classification for avian malaria parasite Plasmodium gallinaceum blood stages by using deep convolutional neural networks.

Scientific reports
The infection of an avian malaria parasite (Plasmodium gallinaceum) in domestic chickens presents a major threat to the poultry industry because it causes economic loss in both the quality and quantity of meat and egg production. Computer-aided diagn...