AIMC Topic: Neural Networks, Computer

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Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones.

Neural networks : the official journal of the International Neural Network Society
The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symme...

Evaluation of Machine Learning Classifiers to Predict Compound Mechanism of Action When Transferred across Distinct Cell Lines.

SLAS discovery : advancing life sciences R & D
Multiparametric high-content imaging assays have become established to classify cell phenotypes from functional genomic and small-molecule library screening assays. Several groups have implemented machine learning classifiers to predict the mechanism...

Convolutional Neural Networks for Radiologic Images: A Radiologist's Guide.

Radiology
Deep learning has rapidly advanced in various fields within the past few years and has recently gained particular attention in the radiology community. This article provides an introduction to deep learning technology and presents the stages that are...

Identification of Diabetic Patients through Clinical and Para-Clinical Features in Mexico: An Approach Using Deep Neural Networks.

International journal of environmental research and public health
Diabetes is a chronic and noncommunicable but preventable disease that is affecting the Mexican population at worrying levels, being the first place in prevalence worldwide. Early diabetes detection has become important to prevent other health condit...

Motion Planning of Autonomous Mobile Robot Using Recurrent Fuzzy Neural Network Trained by Extended Kalman Filter.

Computational intelligence and neuroscience
This paper proposes a novel motion planning method for an autonomous ground mobile robot to address dynamic surroundings, nonlinear program, and robust optimization problems. A planner based on the recurrent fuzzy neural network (RFNN) is designed to...

Features Combined From Hundreds of Midlayers: Hierarchical Networks With Subnetwork Nodes.

IEEE transactions on neural networks and learning systems
In this paper, we believe that the mixed selectivity of neuron in the top layer encodes distributed information produced from other neurons to offer a significant computational advantage over recognition accuracy. Thus, this paper proposes a hierarch...

Clone-Based Encoded Neural Networks to Design Efficient Associative Memories.

IEEE transactions on neural networks and learning systems
In this paper, we introduce a neural network (NN) model named clone-based neural network (CbNN) to design associative memories. Neurons in CbNN can be cloned statically or dynamically which allows to increase the number of data that can be stored and...

Fluorescence microscopy image classification of 2D HeLa cells based on the CapsNet neural network.

Medical & biological engineering & computing
The development of computer technology now allows the quick and efficient automatic fluorescence microscopy generation of a large number of images of proteins in specific subcellular compartments using fluorescence microscopy. Digital image processin...

An unsupervised parameter learning model for RVFL neural network.

Neural networks : the official journal of the International Neural Network Society
With the direct input-output connections, a random vector functional link (RVFL) network is a simple and effective learning algorithm for single-hidden layer feedforward neural networks (SLFNs). RVFL is a universal approximator for continuous functio...

Theories of Error Back-Propagation in the Brain.

Trends in cognitive sciences
This review article summarises recently proposed theories on how neural circuits in the brain could approximate the error back-propagation algorithm used by artificial neural networks. Computational models implementing these theories achieve learning...