[PDF] Top 20 Modeling of stem form and volume through machine learning
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Modeling of stem form and volume through machine learning
... functions and volume equations are essential for estimation of the individual volume, which have consolidated ...dynamic, and may improve the forestry ...accuracy of ... See full document
13
Stem taper modeling and timber volume estimation
... Total stem volume was estimated on the plots through integration of the stem sectional solid by rotation of the taper function (BARRIO ANTA et ...obtained and, ... See full document
8
Exploration of machine learning techniques for automatic optical inspection
... vision and digital image processing [7] to find imperfect object instances within a certain class of forms through a voting ...identification of lines in the image, however, later, this ... See full document
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UNIVERSIDADE FEDERAL DE S ˜AO CARLOS
... capturing and analyzing facial behaviors is lighting ...most of the cameras have visioning problem at night (BERGASA et ...because of the fact that the night cameras don’t have a proper vision in the ... See full document
101
Application of machine learning for real-time evaluation of salinity (or TDS) in drinking water using photonic sensors
... analyse and classify the outputs obtained by the PhC- based sensors’ simulated result and was used to evaluate the ppm level of salinity/TDS in drinking ...probability and as- signs it to the ... See full document
9
Discerning apical and basolateral properties of HT-29/B6 and IPEC-J2 cell layers by impedance spectroscopy, mathematical modeling and machine learning.
... 98% of all measured values were found to lie within the corresponding reference ...evaluation of the two subgroups of model impedance spectra with t ratios # 5 and ...position of the ... See full document
12
Machine learning for biomedical literature triage.
... means of mycoMINE annotation content, their corresponding bio-entities and EC ...group of words. Table 2 lists all the entities annotated by mycoMINE and their corresponding ...[30] and ... See full document
21
Exploration and application of machine learning algorithms to functional connectivity data
... use of the GLM and Gaussian Random Field (GRF) theory to make typical inferences about spatially extended data through statistical parametric maps (Li et ...data and uses GRF to resolve the ... See full document
94
Machine-learning techniques and short-term combination forecasting of industrial production
... scenario and is used by both state and private institutions for ...Institute of Geography and Statistics (IBGE, 2018), but not until approximately 35 days after the reference ...Because ... See full document
10
An assessment of various active learning techniques for classification of remote sensing images
... Indiana and consists of 145times145 pixels and 224 spectral reflectance bands in the wavelength range ...subset of a larger one. The Indian Pines scene consists of two- thirds ... See full document
10
Prediction errors in learning drug response from gene expression data - influence of labeling, sample size, and machine learning algorithm.
... set of different indications and according to their response to different standard ...aim of this study was to compare the NCI60 panel to our panel of 21 cell lines, including 18 tumor cell ... See full document
13
Modeling of Two-Stage Solidification: Part II Computational Verification of the Model
... stage of solidification is the same for both modified and unmodified ...stage of the solidification, the nucleation process unfolds in slightly different way, depending on the eutectic transformation ... See full document
6
Heuristic methods applied in reference evapotranspiration modeling
... as machine learning or pattern recognition algorithms, have presented promising results in the modeling of meteorological parameters (Adnan; Latif; Nazir, 2017; Feng et ...machines and ... See full document
11
Simultaneous Determination Of Adjusted Ranks Of Sample Observations And Their Sums And Products
... sums of squares of ranks are different depending on whether or not there are tied observations in the data and hence are assigned mean ...some of the observations are tied and hence ... See full document
7
OBJECTIONABLE IMAGE DETECTION IN CLOUD COMPUTING PARADIGM-A REVIEW
... detector and add some extra features such as face-skin divided by body-skin and biggest skin patch ...use of skin adaptive models. Find a compact and more knowledgeable way to characterize the ... See full document
7
8th INTREPID Report: The future of university as if sustainability mattered: A co-creation experience through Theory U journey
... One of the key ideas that underlies the Theory U methodology, is that the future is already ...sense and actualize it more fully. The question, of course is how do you do that? For this reason the ... See full document
27
A INTELIGÊNCIA ARTIFICIAL - IA
... Data, Machine Learning, Deep Learning, Python Programming Language, sistema R, entre outros, todos derivados de otimizadores de processos, que através algoritmos e jurismetria oferecem aos Operadores ... See full document
9
Risk assessment of atmospheric emissions using machine learning
... the form of Gaussian functions, and Sutton (1932) obtained a Gaussian function as a solution of the Fickian equation with an “effective eddy” varying with the distance traveled by the ... See full document
10
Rev. bras. linguist. apl. vol.11 número2
... effect of variable permutation also indicates that, apparently, individual predictors are not that ...consequence of the correlational structure characterizing the predictor ...each of the predictors ... See full document
34
Adversarial machine learning: denial of services recognition
... set of evolutionary algorithms which take inspiration from genetic evolution observed in living ...set of individuals (data), and through processes of mutation and reproduction ... See full document
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