AIMC Topic: Support Vector Machine

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A Robust Feature Extraction Model for Human Activity Characterization Using 3-Axis Accelerometer and Gyroscope Data.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) using embedded sensors in smartphones and smartwatch has gained popularity in extensive applications in health care monitoring of elderly people, security purpose, robotics, monitoring employees in the industry, and o...

Nondestructive Classification of Soybean Seed Varieties by Hyperspectral Imaging and Ensemble Machine Learning Algorithms.

Sensors (Basel, Switzerland)
During the processing and planting of soybeans, it is greatly significant that a reliable, rapid, and accurate technique is used to detect soybean varieties. Traditional chemical analysis methods of soybean variety sampling (e.g., mass spectrometry a...

A deep facial recognition system using computational intelligent algorithms.

PloS one
The development of biometric applications, such as facial recognition (FR), has recently become important in smart cities. Many scientists and engineers around the world have focused on establishing increasingly robust and accurate algorithms and met...

A machine learning-based clinical tool for diagnosing myopathy using multi-cohort microarray expression profiles.

Journal of translational medicine
BACKGROUND: Myopathies are a heterogenous collection of disorders characterized by dysfunction of skeletal muscle. In practice, myopathies are frequently encountered by physicians and precise diagnosis remains a challenge in primary care. Molecular e...

Essential gene prediction using limited gene essentiality information-An integrative semi-supervised machine learning strategy.

PloS one
Essential gene prediction helps to find minimal genes indispensable for the survival of any organism. Machine learning (ML) algorithms have been useful for the prediction of gene essentiality. However, currently available ML pipelines perform poorly ...

Proximal Methods for Plant Stress Detection Using Optical Sensors and Machine Learning.

Biosensors
Plant stresses have been monitored using the imaging or spectrometry of plant leaves in the visible (red-green-blue or RGB), near-infrared (NIR), infrared (IR), and ultraviolet (UV) wavebands, often augmented by fluorescence imaging or fluorescence s...

Machine learning model for predicting malaria using clinical information.

Computers in biology and medicine
BACKGROUND: Rapid diagnosing is crucial for controlling malaria. Various studies have aimed at developing machine learning models to diagnose malaria using blood smear images; however, this approach has many limitations. This study developed a machin...

PupStruct: Prediction of Pupylated Lysine Residues Using Structural Properties of Amino Acids.

Genes
Post-translational modification (PTM) is a critical biological reaction which adds to the diversification of the proteome. With numerous known modifications being studied, pupylation has gained focus in the scientific community due to its significant...

Classification of malignant tumors in breast ultrasound using a pretrained deep residual network model and support vector machine.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In this study, a transfer learning method was utilized to recognize and classify benign and malignant breast tumors, using two-dimensional breast ultrasound (US) images, to decrease the effort expended by physicians and improve the quality of clinica...