AIMC Topic: Neural Networks, Computer

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Music Score Recognition Method Based on Deep Learning.

Computational intelligence and neuroscience
In recent years, the recommendation application of artificial intelligence and deep music has gradually become a research hotspot. As a complex machine learning algorithm, deep learning can extract features with value laws through training samples. T...

Construction of Garden Landscape Design System Based on Multimodal Intelligent Computing and Deep Neural Network.

Computational intelligence and neuroscience
The problem of module discrimination and identification in the field of landscape design is the focus of researchers. Based on multimodal intelligent computing, this paper constructs a landscape design system based on deep neural network. The article...

Robust Fixed-Time H∞ Trajectory Tracking Control for Marine Surface Vessels Based on a Self-Structuring Neural Network.

Computational intelligence and neuroscience
In this study, a robust fixed-time H∞ trajectory tracking controller for marine surface vessels (MSVs) is proposed based on self-structuring neural network (SSNN). First, a fixed-time H Lyapunov stability theorem is proposed to guarantee that the MSV...

Feasibility Analysis of Mutual Benefit Cooperation between Environment-Embedded Art Design Education and Local SMEs Development Based on Improved Grey Analysis.

Journal of environmental and public health
With the continuous progress of the economic era, both art and design education and local small and medium-sized enterprises are facing the crisis of survival and the pressure of competition, forcing the two to join hands to resist this crisis. The p...

Rainfall prediction using multiple inclusive models and large climate indices.

Environmental science and pollution research international
Rainfall prediction is vital for the management of available water resources. Accordingly, this study used large lagged climate indices to predict rainfall in Iran's Sefidrood basin. A radial basis function neural network (RBFNN) and a multilayer per...

eICAB: A novel deep learning pipeline for Circle of Willis multiclass segmentation and analysis.

NeuroImage
BACKGROUND: The accurate segmentation, labeling and quantification of cerebral blood vessels on MR imaging is important for basic and clinical research, yet results are not generalizable, and often require user intervention. New methods are needed to...

cACP-DeepGram: Classification of anticancer peptides via deep neural network and skip-gram-based word embedding model.

Artificial intelligence in medicine
Cancer is a Toxic health concern worldwide, it happens when cellular modifications cause the irregular growth and division of human cells. Several traditional approaches such as therapies and wet laboratory-based methods have been applied to treat ca...

Applicability analysis of immunotherapy for lung cancer patients based on deep learning.

Methods (San Diego, Calif.)
According to global and Chinese cancer statistics, lung cancer is the second most common cancer globally with the highest mortality rate and a severe threat to human life and health. In recent years, immunotherapy has made significant breakthroughs i...

Double-branch U-Net for multi-scale organ segmentation.

Methods (San Diego, Calif.)
U-Net has achieved great success in the task of medical image segmentation. It encodes and extracts information from several convolution blocks, and then decodes the feature maps to get the segmentation results. Our experiments show that in a multi-s...

Physics-informed neural networks for hydraulic transient analysis in pipeline systems.

Water research
In water pipeline systems, monitoring and predicting hydraulic transient events are important to ensure the proper operation of pressure control devices (e.g., pressure reducing valves) and prevent potential damages to the network infrastructure. Sim...