18 eredmény a kulcsszóra: 'deep learning'
lióval állott magasabban. A leszálmitol't váltók és előlegek állaga a mult évi 554 millióról 32 millió- val 521'3 millióra esett. Az előző havival szemben azonban 63
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Hat vastagbél tumoros (közepesen differenciált, bal oldali, II. stádiumú) beteg sebészeti mintájából izolált RNS minta reverz transzkripcióját követően,
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Igen nagy békességestüréssel voltának az О Testa- mentomi hivek, legfőképen Jób, mind az által nem vala nékik ollyan vi- gasztalások, mint az Uj Testamentomi Híveknek, azért
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For studying the effect of SEPT9 methylation on protein expression, 10 healthy, 14 adenoma (villous and tubulovillous) and 13 colorectal cancer (stage II and III) biopsy
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Numerous documents aiming to establish the legal framework for cross- border cooperation have been produced, including the Madrid Convention (1980) and the
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Mead és mtsai [157] egészséges, adenomás és tumoros páciensek plazma mintáiból határozták meg a keringő szabad DNS szintet, és szignifikáns különbséget
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• Has deep knowledge of scientific theories of learning, the strategies and methods of learning and the methods of supporting learning and teaching, has an understanding
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We reviewed deep learning and traditional machine learning models’ papers for sentiment analysis; most machine learning models either used Naïve Bayes or SVM algorithms to classify
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• Has deep knowledge of scientific theories of learning, the strategies and methods of learning and the methods of supporting learning and teaching.. Has an understanding of the
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anatomy region recognition, deep learning, image classification, imaging informatics, medical image processing..
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3 Program “Ethanol” (adopted on 4.07.2000); Conception of the Program for biodiesel production till 2010 (adopted on 28.12.05); Program for biodiesel production till 2010
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• Has deep knowledge of scientific theories of learning, the strategies and methods of learning and teaching, has an understanding of the role of various
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In [13], the authors proposed a joint deep learning framework and a new deep network architecture that jointly learns feature extraction, deformation handling, occlusion handling,
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In [13], the authors proposed a joint deep learning framework and a new deep network architecture that jointly learns feature extraction, deformation handling, occlusion handling,
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Traditional algorithms in person re-identification are usually based on hand-crafted feature extraction and distance metric learning.. Deep learning architectures have captured
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1: In each episode, the agent re- ceives the initial conditions and the target for trajec- tory planning and calculates the interior points of the trajectory, then we drive a
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Limiting oxygen index test (L.O.I) and differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FTIR), and scanning electron microscope
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