AIMC Topic: Neural Networks, Computer

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iTIS-PseKNC: Identification of Translation Initiation Site in human genes using pseudo k-tuple nucleotides composition.

Computers in biology and medicine
Translation is an essential genetic process for understanding the mechanism of gene expression. Due to the large number of protein sequences generated in the post-genomic era, conventional methods are unable to identify Translation Initiation Site (T...

Synchronization transitions induced by the fluctuation of adaptive coupling strength in delayed Newman-Watts neuronal networks.

Bio Systems
Introducing adaptive coupling in delayed neuronal networks and regulating the dissipative parameter (DP) of adaptive coupling by noise, we study the effect of fluctuations of the changing rate of adaptive coupling on the synchronization of the neuron...

Impact of sub and supra-threshold adaptation currents in networks of spiking neurons.

Journal of computational neuroscience
Neuronal adaptation is the intrinsic capacity of the brain to change, by various mechanisms, its dynamical responses as a function of the context. Such a phenomena, widely observed in vivo and in vitro, is known to be crucial in homeostatic regulatio...

An Automatic Learning-Based Framework for Robust Nucleus Segmentation.

IEEE transactions on medical imaging
Computer-aided image analysis of histopathology specimens could potentially provide support for early detection and improved characterization of diseases such as brain tumor, pancreatic neuroendocrine tumor (NET), and breast cancer. Automated nucleus...

Analyzing animal behavior via classifying each video frame using convolutional neural networks.

Scientific reports
High-throughput analysis of animal behavior requires software to analyze videos. Such software analyzes each frame individually, detecting animals' body parts. But the image analysis rarely attempts to recognize "behavioral states"-e.g., actions or f...

RBoost: Label Noise-Robust Boosting Algorithm Based on a Nonconvex Loss Function and the Numerically Stable Base Learners.

IEEE transactions on neural networks and learning systems
AdaBoost has attracted much attention in the machine learning community because of its excellent performance in combining weak classifiers into strong classifiers. However, AdaBoost tends to overfit to the noisy data in many applications. Accordingly...

Artificial Neural Network applied as a methodology of mosquito species identification.

Acta tropica
There are about 200 species of mosquitoes (Culicidae) known to be vectors of pathogens that cause diseases in humans. Correct identification of mosquito species is an essential step in the development of effective control strategies for these disease...

Forecasting PM10 in Algiers: efficacy of multilayer perceptron networks.

Environmental science and pollution research international
Air quality forecasting system has acquired high importance in atmospheric pollution due to its negative impacts on the environment and human health. The artificial neural network is one of the most common soft computing methods that can be pragmatic...

Synchronization of a Class of Switched Neural Networks with Time-Varying Delays via Nonlinear Feedback Control.

IEEE transactions on cybernetics
This paper is concerned with the synchronization problem for a class of switched neural networks (SNNs) with time-varying delays. First, a new crucial lemma which includes and extends the classical exponential stability theorem is constructed. Then b...

High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

International journal of neural systems
Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the ...