Surveys

Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging.

The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vector machine regression (WT-LSSVR) is proposed to select the optimal wavelength and establish the detection model. The Vis-NIR hyperspectral images of 40...

An extensive experimental survey of regression methods.

Regression is a very relevant problem in machine learning, with many different available approaches. The current work presents a comparison of a large collection composed by 77 popular regression models which belong to 19 families: linear and generalized linear models, generalized additive models, least squares, projection methods, LASSO and ridge regression, Bayesian models, Gaussian processes, q...

Unsupervised Person Re-Identification by Deep Asymmetric Metric Embedding.

Person re-identification (Re-ID) aims to match identities across non-overlapping camera views. Researchers have proposed many supervised Re-ID models ...

Ascertaining Depression Severity by Extracting Patient Health Questionnaire-9 (PHQ-9) Scores from Clinical Notes.

The Patient Health Questionnaire-9 (PHQ-9) is a validated instrument for assessing depression severity. While some electronic health record (EHR) syst...

Image Processing-Based Recognition of Wall Defects Using Machine Learning Approaches and Steerable Filters.

Detection of defects including cracks and spalls on wall surface in high-rise buildings is a crucial task of buildings' maintenance. If left undetecte...

Predicting the Health Status of an Unmanned Aerial Vehicles Data-Link System Based on a Bayesian Network.

Unmanned aerial vehicles (UAVs) require data-link system to link ground data terminals to the real-time controls of each UAV. Consequently, the abilit...

A Novel Classification and Identification Scheme of Emitter Signals Based on Ward's Clustering and Probabilistic Neural Networks with Correlation Analysis.

The rapid development of modern communication technology makes the identification of emitter signals more complicated. Based on Ward's clustering and ...

Automatic glomerular identification and quantification of histological phenotypes using image analysis and machine learning.

Current methods of scoring histological kidney samples, specifically glomeruli, do not allow for collection of quantitative data in a high-throughput ...

Comparison of Visual Prostate Symptom Score with the International Prostate Symptom Score and uroflowmetry parameters in assessing men with lower urinary tract symptoms in Dr. Cipto Mangunkusumo National General Hospital, Indonesia.

BACKGROUND: The complexity of International Prostate Symptom Score (IPSS) as an objective questionnaire for lower urinary tract symptoms might be over...

How Specific Abilities Might Throw '' a Curve: An Idea on How to Capitalize on the Predictive Validity of Specific Cognitive Abilities.

School grades are still used by universities and employers for selection purposes. Thus, identifying determinants of school grades is important. Broad...

Management practices associated with strongylid parasite prevalence on horse farms in rural counties of Kentucky.

Anthelmintic resistance among cyathostomin parasites is a wide-spread problem. The parasite control guidelines written by the American Association of ...

Prediction of Periventricular Leukomalacia in Neonates after Cardiac Surgery Using Machine Learning Algorithms.

Periventricular leukomalacia (PVL) is brain injury that develops commonly in neonates after cardiac surgery. Earlier identification of patients who ar...

Is there a symptomatic distinction between the affective psychoses and schizophrenia? A machine learning approach.

Dubiety exists over whether clinical symptoms of schizophrenia can be distinguished from affective psychosis, the assumption being that absence of a "...

Assessing Wrist Movement With Robotic Devices.

Robotic devices have been proposed to meet the rising need for high intensity, long duration, and goal-oriented therapy required to regain motor funct...

Semantic measures: Using natural language processing to measure, differentiate, and describe psychological constructs.

Psychological constructs, such as emotions, thoughts, and attitudes are often measured by asking individuals to reply to questions using closed-ended ...

UAVs, Hyperspectral Remote Sensing, and Machine Learning Revolutionizing Reef Monitoring.

Recent advances in unmanned aerial system (UAS) sensed imagery, sensor quality/size, and geospatial image processing can enable UASs to rapidly and co...

On the importance of hidden bias and hidden entropy in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines.

In this paper, we analyze the role of hidden bias in representational efficiency of the Gaussian-Bipolar Restricted Boltzmann Machines (GBPRBMs), whic...

Factors influencing unsafe behaviors: A supervised learning approach.

Despite its potential, the use of machine learning in safety studies had been limited. Considering machine learning's advantage in predictive accuracy...

Reliability, validity, and clinical feasibility of a rapid and objective assessment of post-stroke deficits in hand proprioception.

BACKGROUND: Proprioceptive function can be affected after neurological injuries such as stroke. Severe and persistent proprioceptive impairments may b...

An On-Chip Trainable and the Clock-Less Spiking Neural Network With 1R Memristive Synapses.

Spiking neural networks (SNNs) are being explored in an attempt to mimic brain's capability to learn and recognize at low power. Crossbar architecture...