AIMC Topic: Neural Networks, Computer

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GAIN: A Gated Adaptive Feature Interaction Network for Click-Through Rate Prediction.

Sensors (Basel, Switzerland)
CTR (Click-Through Rate) prediction has attracted more and more attention from academia and industry for its significant contribution to revenue. In the last decade, learning feature interactions have become a mainstream research direction, and dozen...

Prediction Models for Railway Track Geometry Degradation Using Machine Learning Methods: A Review.

Sensors (Basel, Switzerland)
Keeping railway tracks in good operational condition is one of the most important tasks for railway owners. As a result, railway companies have to conduct track inspections periodically, which is costly and time-consuming. Due to the rapid developmen...

Validation and Improvement of a Convolutional Neural Network to Predict the Involved Pathology in a Head and Neck Surgery Cohort.

International journal of environmental research and public health
The selection of patients for the constitution of a cohort is a major issue for clinical research (prospective studies and retrospective studies in real life). Our objective was to validate in real life conditions the use of a Deep Learning process b...

General object-based features account for letter perception.

PLoS computational biology
After years of experience, humans become experts at perceiving letters. Is this visual capacity attained by learning specialized letter features, or by reusing general visual features previously learned in service of object categorization? To explore...

Tool Cutting Force Prediction Model Based on ALO-ELM Algorithm.

Computational intelligence and neuroscience
Aiming at the problems of low learning efficiency, slow convergence speed, and low prediction accuracy of traditional data-driven model applied to tool cutting force prediction, a prediction method of tool cutting force based on ant lion optimizer (A...

BDS-3 Broadcast Ephemeris Orbit Correction Model Based on Improved PSO Combined with BP Neural Network.

Computational intelligence and neuroscience
During the operation of navigation satellites, errors in the broadcast ephemeris orbits are caused by the influence of ingress factors and other factors. To address this phenomenon, this paper examines the use of the computational intelligence (CI) m...

The Application of Computer Intelligence in the Cyber-Physical Business System Integration in Network Security.

Computational intelligence and neuroscience
In order to address the false alarm detection problem caused by the inability to identify the transgression scene pages in the process of horizontal transgression detection, this study proposes a deep learning-based LSTM-AutoEncoder unsupervised pred...

A Study on the Application of BP Neural Network Based on Visual Recognition in Regional Economic Forecasting.

Computational intelligence and neuroscience
The economic growth in the new normal is no longer limited to the total amount and scale of economic growth in the traditional and neoclassical periods, but has changed to "quality" and "development" under the dual requirements of historical changes ...

Primary Investigation of Deep Learning Models for Japanese "Group Classification" of Whole-Slide Images of Gastric Endoscopic Biopsy.

Computational and mathematical methods in medicine
BACKGROUND: Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the opportunity of early diagnosis and treatment of gastric cancer. The Japanese "Group classification" of gastric biopsy corresponds well with the endosco...

How to incorporate biological insights into network models and why it matters.

The Journal of physiology
Due to the staggering complexity of the brain and its neural circuitry, neuroscientists rely on the analysis of mathematical models to elucidate its function. From Hodgkin and Huxley's detailed description of the action potential in 1952 to today, ne...