AIMC Topic: Support Vector Machine

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Remote Sensing Image Recognition Based on LOG-T-SSA-LSSVM and AE-ELM Network.

Computational intelligence and neuroscience
Aiming at the influence of different working conditions on recognition accuracy in remote sensing image recognition, this paper adopts hierarchical strategy to construct a network. Firstly, in order to establish the classification relationship betwee...

Application research of pulse signal physiology and pathology feature mining in the field of disease diagnosis.

Computer methods in biomechanics and biomedical engineering
This experiment is based on the principle of traditional Chinese medicine (TCM) pulse diagnosis, the human pulse signal collected by the sensor is organized into a dataset, and the algorithms are designed to apply feature extraction. After denoising,...

Internet-based supply chain financing-oriented risk assessment using BP neural network and SVM.

PloS one
To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. Firstly, this paper summarizes 12 risk factors of S...

A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology.

Sports biomechanics
Greater understanding of differences in technique between runners may allow more beneficial feedback related to improving performance and decreasing injury risk. The purpose of this study was to develop and test a support vector machine classifier, w...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Computational and mathematical methods in medicine
Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus increases the mortality rate of humans. Almost 1% of world's population suffers from epileptic seizures....

Deep-learning and radiomics ensemble classifier for false positive reduction in brain metastases segmentation.

Physics in medicine and biology
Stereotactic radiosurgery (SRS) is now the standard of care for brain metastases (BMs) patients. The SRS treatment planning process requires precise target delineation, which in clinical workflow for patients with multiple (>4) BMs (mBMs) could becom...

Microscopic retinal blood vessels detection and segmentation using support vector machine and K-nearest neighbors.

Microscopy research and technique
The retina is the deepest layer of texture covering the rear of the eye, recorded by fundus images. Vessel detection and segmentation are useful in disease diagnosis. The retina's blood vessels could help diagnose maladies such as glaucoma, diabetic ...

Transfer inhibitory potency prediction to binary classification: A model only needs a small training set.

Computer methods and programs in biomedicine
One of the most laborious for drug discovery is to select compounds from a library for experimental evaluation. Hence, we propose a machine learning model only needs to be trained on a small dataset to predict the inhibition constant (Ki) and half ma...

Muscle force estimation from lower limb EMG signals using novel optimised machine learning techniques.

Medical & biological engineering & computing
The main objective of this work is to establish a framework for processing and evaluating the lower limb electromyography (EMG) signals ready to be fed to a rehabilitation robot. We design and build a knee rehabilitation robot that works with surface...