AIMC Topic: Neural Networks, Computer

Clear Filters Showing 4361 to 4370 of 31376 articles

Fluorescence spectroscopy combined with multilayer perceptron deep learning to identify the authenticity of monofloral honey-Rape honey.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Honey authenticity is critical to honey quality. The development of a quick, easy, and non-destructive technique for determining the authenticity of honey encourages an improvement in honey quality. Here, the authenticity of monofloral honey-rape hon...

Multimodal fish maw type recognition based on Wasserstein generative adversarial network combined with gradient penalty and spectral fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
There are many types of fish maw with significantly varying prices. The specific type directly affects its market value and medicinal efficacy. This paper proposes a fish maw type recognition method based on Wasserstein generative adversarial network...

Weakly supervised label learning flows.

Neural networks : the official journal of the International Neural Network Society
Supervised learning usually requires a large amount of labeled data. However, attaining ground-truth labels is costly for many tasks. Alternatively, weakly supervised methods learn with cheap weak signals that only approximately label some data. Many...

Simultaneous monitoring of two comprehensive quality evaluation indexes of frozen-thawed beef meatballs using hyperspectral imaging and multi-task convolutional neural network.

Meat science
The quality of beef meatballs during repeated freeze-thaw (F-T) cycles was assessed by multiple indicators. This study introduced a novel quality evaluation method using hyperspectral imaging (HSI) and multi-task learning. Seventeen quality indicator...

A comprehensive review on the application of neural network model in microbial fermentation.

Bioresource technology
The development of high-performance strains and the continuous breakthrough of strain screening technology also pose challenges to downstream fermentation optimization and scale-up. Therefore, neural network models are utilized to optimize the fermen...

A deep learning model of dorsal and ventral visual streams for DVSD.

Scientific reports
Artificial intelligence (AI) methods attempt to simulate the behavior and the neural activity of the brain. In particular, Convolutional Neural Networks (CNNs) offer state-of-the-art models of the ventral visual stream. Furthermore, no proposed model...

Complexities of feature-based learning systems, with application to reservoir computing.

Neural networks : the official journal of the International Neural Network Society
This paper studies complexity measures of reservoir systems. For this purpose, a more general model that we call a feature-based learning system, which is the composition of a feature map and of a final estimator, is studied. We study complexity meas...

TSOM: Small object motion detection neural network inspired by avian visual circuit.

Neural networks : the official journal of the International Neural Network Society
Detecting small moving objects in complex backgrounds from an overhead perspective is a highly challenging task for machine vision systems. As an inspiration from nature, the avian visual system is capable of processing motion information in various ...

Outer synchronization and outer H synchronization for coupled fractional-order reaction-diffusion neural networks with multiweights.

Neural networks : the official journal of the International Neural Network Society
This paper introduces multiple state or spatial-diffusion coupled fractional-order reaction-diffusion neural networks, and discusses the outer synchronization and outer H synchronization problems for these coupled fractional-order reaction-diffusion ...

Evolutionary architecture search for generative adversarial networks using an aging mechanism-based strategy.

Neural networks : the official journal of the International Neural Network Society
Generative Adversarial Networks (GANs) have emerged as a key technology in artificial intelligence, especially in image generation. However, traditionally hand-designed GAN architectures often face significant training stability challenges, which are...