AIMC Topic: Neural Networks, Computer

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Cluster stochastic synchronization of complex dynamical networks via fixed-time control scheme.

Neural networks : the official journal of the International Neural Network Society
By means of fixed-time (FDT) control technique, cluster stochastic synchronization of complex networks (CNs) is investigated. Quantized controller is designed to realize the synchronization of CNs within a settling time. FDT synchronization criteria ...

Quantification of interfacial energies associated with membrane fouling in a membrane bioreactor by using BP and GRNN artificial neural networks.

Journal of colloid and interface science
Interfacial energy between sludge foulants and rough membrane surface critically determines adhesive fouling in membrane bioreactors (MBRs). As a current available method, the advanced extensive Derjaguin-Landau-Verwey-Overbeek (XDLVO) approach canno...

Spacial sampled-data control for H output synchronization of directed coupled reaction-diffusion neural networks with mixed delays.

Neural networks : the official journal of the International Neural Network Society
This work investigates the H output synchronization (HOS) of the directed coupled reaction-diffusion (R-D) neural networks (NNs) with mixed delays. Firstly, a model of the directed state coupled R-D NNs is introduced, which not only contains some dis...

A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we derive a new fixed-time stability theorem based on definite integral, variable substitution and some inequality techniques. The fixed-time stability criterion and the upper bound estimate formula for the settling time are different ...

Crowding reveals fundamental differences in local vs. global processing in humans and machines.

Vision research
Feedforward Convolutional Neural Networks (ffCNNs) have become state-of-the-art models both in computer vision and neuroscience. However, human-like performance of ffCNNs does not necessarily imply human-like computations. Previous studies have sugge...

Evaluating Convolutional Neural Networks for Cage-Free Floor Egg Detection.

Sensors (Basel, Switzerland)
The manual collection of eggs laid on the floor (or 'floor eggs') in cage-free (CF) laying hen housing is strenuous and time-consuming. Using robots for automatic floor egg collection offers a novel solution to reduce labor yet relies on robust egg d...

A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Human face image analysis is an active research area within computer vision. In this paper we propose a framework for face image analysis, addressing three challenging problems of race, age, and gender recognition through face parsing. We manually la...

Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.

Communications biology
Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysi...

ProDCoNN: Protein design using a convolutional neural network.

Proteins
Designing protein sequences that fold to a given three-dimensional (3D) structure has long been a challenging problem in computational structural biology with significant theoretical and practical implications. In this study, we first formulated this...

Radon Inversion via Deep Learning.

IEEE transactions on medical imaging
The Radon transform is widely used in physical and life sciences, and one of its major applications is in medical X-ray computed tomography (CT), which is significantly important in disease screening and diagnosis. In this paper, we propose a novel r...