A protocol for automated timber species identification using metabolome profiling
Sign Up to like & getrecommendations! Published in 2019 at "Wood Science and Technology"
DOI: 10.1007/s00226-019-01111-1
Abstract: Using chemical fingerprints for timber species identification is a relatively new, but promising technique. However, little is known about the effect of pre-processing spectral data parameter settings on the timber species classification accuracy. Therefore, this… read more here.
Keywords: timber species; species identification; classification accuracy; parameter ... See more keywords
Entropy with Local Binary Patterns for Efficient Iris Liveness Detection
Sign Up to like & getrecommendations! Published in 2018 at "Wireless Personal Communications"
DOI: 10.1007/s11277-017-5089-z
Abstract: Iris anti-spoofing is one of the most important topics, in which the development is increasing rapidly. This paper introduces an efficient system for detecting iris attacks. The system avoids the segmentation and the normalization stages… read more here.
Keywords: local binary; system; detection; classification accuracy ... See more keywords
Developing Transformed Fuzzy Neural Networks to Enhance Medical Data Classification Accuracy
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Fuzzy Systems"
DOI: 10.1007/s40815-018-0503-6
Abstract: Abstract Developing an automatic model to precisely and quickly classify medical data is a challenging work due to lack of medical knowledge. This paper presented a transformed fuzzy neural network (TFNN) to enhance medical data… read more here.
Keywords: classification; classification accuracy; data classification; transformed fuzzy ... See more keywords
Classifying running speed conditions using a single wearable sensor: Optimal segmentation and feature extraction methods.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of biomechanics"
DOI: 10.1016/j.jbiomech.2018.01.034
Abstract: Accelerometers have been used to classify running patterns, but classification accuracy and computational load depends on signal segmentation and feature extraction. Stride-based segmentation relies on identifying gait events, a step avoided by using window-based segmentation.… read more here.
Keywords: computational load; feature; segmentation; classification accuracy ... See more keywords
Laser desorption tissue imaging with Differential Mobility Spectrometry.
Sign Up to like & getrecommendations! Published in 2022 at "Experimental and molecular pathology"
DOI: 10.1016/j.yexmp.2022.104759
Abstract: Pathological gross examination of breast carcinoma samples is sometimes laborious. A tissue pre-mapping method could indicate neoplastic areas to the pathologist and enable focused sampling. Differential Mobility Spectrometry (DMS) is a rapid and affordable technology… read more here.
Keywords: breast; mobility spectrometry; tissue; differential mobility ... See more keywords
Critical item (CR) analysis expands the classification accuracy of performance validity tests based on the forced choice paradigm-Replicating previously introduced CR cutoffs within the Word Choice Test.
Sign Up to like & getrecommendations! Published in 2022 at "Neuropsychology"
DOI: 10.1037/neu0000834.supp
Abstract: OBJECTIVE This study was designed to replicate previous research on critical item analysis within the Word Choice Test (WCT). METHOD Archival data were collected from a mixed clinical sample of 119 consecutively referred adults (Mage… read more here.
Keywords: critical item; item analysis; choice; item ... See more keywords
Scoring algorithms for a computer-based cognitive screening tool: An illustrative example of overfitting machine learning approaches and the impact on estimates of classification accuracy.
Sign Up to like & getrecommendations! Published in 2019 at "Psychological assessment"
DOI: 10.1037/pas0000764
Abstract: Computerized cognitive screening tools, such as the self-administered Computerized Assessment of Memory Cognitive Impairment (CAMCI), require little training and ensure standardized administration and could be an ideal test for primary care settings. We conducted a… read more here.
Keywords: machine learning; cross validation; accuracy; classification accuracy ... See more keywords
Neural signatures to emotion-related word stimuli may vary
Sign Up to like & getrecommendations! Published in 2018 at "Nature Human Behaviour"
DOI: 10.1038/s41562-018-0350-3
Abstract: To the Editor — A recent study by Just et al.1 used a Gaussian Naïve Bayes classifier cross-validated with a leave-one-out procedure to correctly classify participants as healthy controls or suicidal ideators with 91% accuracy… read more here.
Keywords: suicidal ideators; classification accuracy; accuracy; neural signatures ... See more keywords
Using Process Data to Improve Classification Accuracy of Cognitive Diagnosis Model.
Sign Up to like & getrecommendations! Published in 2023 at "Multivariate behavioral research"
DOI: 10.1080/00273171.2022.2157788
Abstract: With the advance of computer-based assessments, many process data, such as response times (RTs), action sequences, Eye-tracking data, the log data for collaborative problem-solving (CPS) and mouse click/drag becomes readily available. Findings from previous studies… read more here.
Keywords: model; classification accuracy; process; process data ... See more keywords
Improved Classification Accuracy for Diagnosing the Early Stage of Parkinson’s Disease Using Alpha Stable Distribution
Sign Up to like & getrecommendations! Published in 2021 at "Iete Journal of Research"
DOI: 10.1080/03772063.2021.1910580
Abstract: Early diagnosis of the neurodegenerative disorder Parkinson’s disease (PD) and Scan without Evidence of Dopaminergic Deficit (SWEDD) is essential for effective patient management in neurodisorders,... read more here.
Keywords: parkinson; classification accuracy; improved classification; parkinson disease ... See more keywords
Decoding motor imagery tasks using ESI and hybrid feature CNN
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Neural Engineering"
DOI: 10.1088/1741-2552/ac4ed0
Abstract: Objective. Brain–computer interface (BCI) based on motor imaging electroencephalogram (MI-EEG) can be useful in a natural interaction system. In this paper, a new framework is proposed to solve the MI-EEG binary classification problem. Approach. Electrophysiological… read more here.
Keywords: augment methods; classification; accuracy; motor ... See more keywords