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On a classification of word problems from the first grade Lithuanian textbooks
Published 2021-03-01“…Word problems are classified to S problems and P problems by Verschaffel [9], classification is being specified and expanded. Reviewed word problems in Lithuanian first grade textbooks and divided to types. …”
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Classification of p-adic 6-dimensional filiform Leibniz algebras by solutions of x q = a
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Classification of Crash Pattern Based on Vehicle Acceleration and Prediction Algorithm for Occupant Injury
Published 2013-01-01Get full text
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Conditionally optimal classification based on CFAR and invariance property for blind receivers
Published 2021-03-01Get full text
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Classification of audio signals using spectrogram surfaces and extrinsic distortion measures
Published 2022-10-01Get full text
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Multivariate Discrimination of Czech Autochthonous Horses
Published 2013-09-01“…The tested individuals were assigned with overall 81.9% classification success to correct breed. The best classification result reached Czech Warmblood 95.7%, the black Old Kladruby horse 87.5% and Silesian Noriker, respectively, 85.7%. …”
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Classification, function, and advances in tsRNA in non-neoplastic diseases
Published 2023-11-01Get full text
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Comparison of Supervised-learning Models for Infant Cry Classification / Vergleich von Klassifikationsmodellen zur Säuglingsschreianalyse
Published 2015-06-01“…To determine the ability of classification models to discriminate between healthy infant cries and various cries of infants suffering from several diseases, a literature search for infant cry classification models was performed; 9 classification models were identified that have been used for infant cry classification in the past. …”
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Classification of Westminster Parliamentary constituencies using e-petition data
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Pest Localization Using YOLOv5 and Classification Based on Quantum Convolutional Network
Published 2023-03-01“…The proposed network is trained from scratch with optimal parameters that provide 99.9% classification accuracy. The achieved results are compared to the existing recent methods, which are performed on the same datasets to prove the novelty of the developed model.…”
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MONITORING THE WHEAT, CORN AND COTTON AREAS IN AN EASTERN MEDITERRANEAN AGRICULTURAL BASIN BETWEEN 2007 AND 2013
Published 2016-10-01“…Overall kappa accuracy was derived to be 0.9. Classification results were shown that wheat areas were decreased 35% and corn and cotton areas were increased 49% and 69% respectively. …”
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Leaf Classification and Ranking Method Based on Multi-granularity Feature Fusion
Published 2023-03-01“…Much work has long been devoted to plant leaf classification,but these methods cannot be applied well in real applications,though they may achieve good results in public datasets.Moreover,they are hardly employed to more complex problems,e.g.leaf ranking,which requires the classification of leaves first and then ranking leaves of the same class.This paper proposes a new model for plant leaf classification as well as leaf ranking,which focuses on the granularity information of leaves and integrates multi-level granularity from coarse to fine.Specifically,the model contains two branches,coarse-grained and fine-grained,which are linked by a coarse-fine hybrid loss,prompting the model to progressively learn a coarse-to-fine representation.A multi-step training approach is used,with different levels of features extracted at each step,therefore enabling the fusion of shallow features with deep features.In addition,a geometric channel attention module,which consists of a spatial transformation and a bili-near attention pooling module,is proposed to allow our model to focus on more discriminative local regions in the image and extract more discriminative features.Our method achieves 99.8% and 99.7% classification accuracy on two publicly available leaf classification datasets,Flavia leaf and Swedish leaf,respectively,and 71.9% classification accuracy on our constructed tobacco leaf ranking dataset,both outperform the state-of-the-art methods.…”
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Lightweight image classifier using dilated and depthwise separable convolutions
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Measuring Upper Limb Kinematics of Forehand and Backhand Topspin Drives with IMU Sensors in Wheelchair and Able-Bodied Table Tennis Players
Published 2021-12-01“…Nineteen participants (AB, <i>n</i> = 9; classification 1 (C1), <i>n</i> = 3; C2, <i>n</i> = 3; C3, <i>n</i> = 4) executed 10 forehand and backhand topspin drives. …”
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Classification of cancer cells at the sub-cellular level by phonon microscopy using deep learning
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Prognostic value of metabolic response in breast cancer patients receiving neoadjuvant chemotherapy
Published 2012-01-01“…</p> <p>Results</p> <p>All patients had a significant metabolic response to NAC, and pre- and post-treatment spectra could be discriminated with 87.9%/68.9% classification accuracy by paired/unpaired partial least squares discriminant analysis (PLS-DA) (<it>p </it>< 0.001). …”
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Heart rhythm characterization through induced physiological variables
Published 2017-07-01“…When combined with a simple classifier, this new methodology results in 99.9% classification accuracy for 1-min RR interval time series (n = 7,400), with heart rate accelerations and jerks being the most discriminant variables. …”
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