Results 251 to 260 of about 2,787,600 (274)
Some of the next articles are maybe not open access.
Pediatric Annals, 2004
Registries become more crucial as vaccination schedules become more complex.
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Registries become more crucial as vaccination schedules become more complex.
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Discrete Applied Mathematics, 2017
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Banik, Aritra +3 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Banik, Aritra +3 more
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Clinical Orthopaedics and Related Research, 1981
Patellar tracking patterns were studied in 20 cadaver knees. The predominant pattern (Type 1) found in 17 knees included medial shift and medial tilt of the patella with respect to the tibial tubercle during extension of the knee. The remaining three knees (Type 2) showed a tendency toward lateral shift and tilt.
B, Reider, J L, Marshall, B, Ring
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Patellar tracking patterns were studied in 20 cadaver knees. The predominant pattern (Type 1) found in 17 knees included medial shift and medial tilt of the patella with respect to the tibial tubercle during extension of the knee. The remaining three knees (Type 2) showed a tendency toward lateral shift and tilt.
B, Reider, J L, Marshall, B, Ring
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Keeping track [animal tracking]
Engineering & Technology, 2014Scientists track a wide variety of animals, from butterflies to great white sharks, in order to study how they use their environment, which foods are important and to gain insights into behaviour and condition of the creatures as well as to identify key breeding areas that may need protection.
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Optical track initiator for multitarget tracking
Applied Optics, 1988An optical processor for multitarget track initiation is presented. It uses the Hough transform to detect target tracks in a fixed time independent of the number of tracks present. In new results, we describe how the system produces target position and velocity estimates in linear time (with the number of targets). Tests of the system are presented for
D P, Casasent, J, Slaski
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2005
We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost.
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We consider tracking as a binary classification problem, where an ensemble of weak classifiers is trained online to distinguish between the object and the background. The ensemble of weak classifiers is combined into a strong classifier using AdaBoost.
openaire +2 more sources