AIMC Topic: Algorithms

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The Time-of-Arrival Offset Estimation in Neural Network Atomic Denoising in Wireless Location.

Sensors (Basel, Switzerland)
With the increasing demand for wireless location services, it is of great interest to reduce the deployment cost of positioning systems. For this reason, indoor positioning based on WiFi has attracted great attention. Compared with the received signa...

A Novel Efficient Convolutional Neural Algorithm for Multi-Category Aliasing Hardware Recognition.

Sensors (Basel, Switzerland)
When performing robotic automatic sorting and assembly operations of multi-category hardware, there are some problems with the existing convolutional neural network visual recognition algorithms, such as large computing power consumption, low recogni...

Classification of multi-lead ECG with deep residual convolutional neural networks.

Physiological measurement
. Automatic electrocardiogram (ECG) interpretation based on deep learning methods is attracting increasing attention. In this study, we propose a novel method to accurately classify multi-lead ECGs using deep residual neural networks.. ECG recordings...

Analysis Model of Image Colour Data Elements Based on Deep Neural Network.

Computational intelligence and neuroscience
At present, the classification method used in image colour element analysis in China is still based on subjective visual evaluation. Because the evaluation process will inevitably be disturbed by human factors, it will not only have low efficiency bu...

Intelligent Measurement and Analysis of Sewage Treatment Parameters based on Fuzzy Neural Algorithm with ARM9 Core CPU.

Computational intelligence and neuroscience
After entering the new century, the state continues to increase the construction of urban sewage treatment projects in response to the deteriorating water pollution situation. How to collect and analyze the sewage parameter variables in the sewage tr...

TSTELM: Two-Stage Transfer Extreme Learning Machine for Unsupervised Domain Adaptation.

Computational intelligence and neuroscience
As a single-layer feedforward network (SLFN), extreme learning machine (ELM) has been successfully applied for classification and regression in machine learning due to its faster training speed and better generalization. However, it will perform poor...

Deep Sentiment Analysis of Twitter Data Using a Hybrid Ghost Convolution Neural Network Model.

Computational intelligence and neuroscience
Several problems remain, despite the evident advantages of sentiment analysis of public opinion represented on Twitter and Facebook. On complicated training data, hybrid approaches may reduce sentiment mistakes. This research assesses the dependabili...

Auxiliary Pneumonia Classification Algorithm Based on Pruning Compression.

Computational and mathematical methods in medicine
Pneumonia infection is the leading cause of death in young children. The commonly used pneumonia detection method is that doctors diagnose through chest X-ray, and external factors easily interfere with the results. Assisting doctors in diagnosing pn...

Hardware-in-the-loop implementation of an unknown input observer for synchronous reluctance motor.

ISA transactions
In this paper, we design a proportional integral observe for a nonlinear synchronous reluctance motor described by a Takagi-Sugeno multi-model. In this design, both states and unknown inputs are estimated simultaneously. First, the mathematical nonli...

Validation of a natural language processing algorithm to identify adenomas and measure adenoma detection rates across a health system: a population-level study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Measuring adenoma detection rates (ADRs) at the population level is challenging because pathology reports are often reported in an unstructured format; further, there is significant variation in reporting methods across instituti...