AIMC Topic: Neural Networks, Computer

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Design of Financial Risk Control Model Based on Deep Learning Neural Network.

Computational intelligence and neuroscience
In recent years, with the continuous increase of financial business, the risk of business is on the rise. Among them, major risk cases are frequent, the cases are increasingly complex, and the means of committing crimes are concealed. The main resear...

Motion Recognition Based on Deep Learning and Human Joint Points.

Computational intelligence and neuroscience
In order to solve the problem that the traditional feature extraction methods rely on manual design, the research method is changed from the traditional method to the deep learning method based on convolutional neural networks. The experimental resul...

Exploration of Stock Portfolio Investment Construction Using Deep Learning Neural Network.

Computational intelligence and neuroscience
To study the intelligent and efficient stock portfolio in China's financial market, based on the relevant theories such as deep learning (DL) neural network (NN) and stock portfolio, this study selects 111 stable stocks from the constituent stocks of...

Performance Evaluation of Knowledge Sharing in an Industry-University-Research Alliance Based on PSO-BPNN.

Computational intelligence and neuroscience
Knowledge sharing performance is very important to evaluate the interests of industry university research alliance. Firstly, this paper puts forward the index system of knowledge sharing performance evaluation of industry university research alliance...

Application of BP Neural Networks in Garment Pattern Design System.

Computational intelligence and neuroscience
With the intensification of global market competition and the continuous development of the information technology, competition in the apparel market has become increasingly fierce. The key to whether China's garment industry can maintain its advanta...

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks.

PloS one
Development of automated analysis tools for "single ion channel" recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1...

Guaranteed cost-based feedback control design for fractional-order neutral systems with input-delayed and nonlinear perturbations.

ISA transactions
Time delay in actuators is mainly caused by electrical and mechanical components. The effect is visible in the system response particularly when changing in the input command. Therefore, input delay is a problem in the control system design that must...

A deep learning-based approach for the diagnosis of adrenal adenoma: a new trial using CT.

The British journal of radiology
OBJECTIVE: To develop and validate deep convolutional neural network (DCNN) models for the diagnosis of adrenal adenoma (AA) using CT.

End-to-End Sentence-Level Multi-View Lipreading Architecture with Spatial Attention Module Integrated Multiple CNNs and Cascaded Local Self-Attention-CTC.

Sensors (Basel, Switzerland)
Concomitant with the recent advances in deep learning, automatic speech recognition and visual speech recognition (VSR) have received considerable attention. However, although VSR systems must identify speech from both frontal and profile faces in re...

Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts.

Sensors (Basel, Switzerland)
Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resour...