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Wyszukujesz frazę "lance" wg kryterium: Temat


Tytuł:
A unique dentary suggests a third genus of batrachosauroidid salamander existed during the latest Cretaceous in the western USA
Autorzy:
Gardner, James D.
Tematy:
Lissamphibia
Caudata
Batrachosauroididae
Cretaceous
Maastrichtian
Lance Formation
North America
Pokaż więcej
Wydawca:
Polska Akademia Nauk. Instytut Paleobiologii PAN
Powiązania:
https://bibliotekanauki.pl/articles/2216212.pdf  Link otwiera się w nowym oknie
Opis:
An incomplete salamander dentary (AMNH FARB 22965) described herein from the upper Maastrichtian Lance Formation, Wyoming, USA, exhibits a puzzling suite of features. Four features—a prominent bony trough extending anteriorly and curving upwards along the lingual surface of the ramus, lack of an obvious Meckelian fossa or groove, an apparent gap in the tooth row, and a symphysial-like first tooth—are likely anomalies. However, the remaining features are interpreted as normal structures and suggest that AMNH FARB 22965 represents a new genus and species of batrachosauroidid, an extinct family of neotenic salamanders that were prominent components of Cretaceous to Neogene freshwater and floodplain paleocommunities in North America and Europe. The new taxon differs from other batrachosauroidids in a unique suite of dentary and dental features, most notably in having a lingual bony flange paralleling the posterior two-thirds of the dentary tooth row, a prominent and robust coronoid process bearing a grooved anterior face, and the anterior portion of the corpus dentalis behind the symphysis is broadly expanded ventrolingually. The presence of a third batrachosauroidid taxon in the Lance Formation was unexpected, considering that the formation has been well sampled and that its two previously recognized batrachosauroidids, namely Opisthotriton kayi and Prodesmodon copei, are known by abundant isolated bones, including dozens of dentaries, from numerous localities in the unit and elsewhere in the North American Western Interior. Known by a unique dentary from the Bushy Tailed Blowout locality, the taxon represented by AMNH FARB 22965 evidently was uncommon within the Lance Formation paleoenvironment.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An efficient pedestrian attribute recognition system under challenging conditions
Autorzy:
Nguyen, Ha X.
Hoang, Dong N.
Tran, Tuan A.
Dang, Tuan M.
Tematy:
pedestrian attribute recognition
Deep Learning
vision transformer
security surveil-lance
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Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Instytut Informatyki Technicznej
Powiązania:
https://bibliotekanauki.pl/articles/24200444.pdf  Link otwiera się w nowym oknie
Opis:
In this work, an efficient pedestrian attribute recognition system is introduced. The system is based on a novel processing pipeline that combines the best-performing attribute extraction model with an efficient attribute filtering algorithm using keypoints of human pose. The attribute extraction models are developed based on several state-of-the-art deep networks via transfer learning techniques, including ResNet50, Swin-transformer, and ConvNeXt. Pre-trained models of these networks are fine-tuned using the Ensemble Pedestrian Attribute Recognition (EPAR) dataset. Several optimization techniques, including the advanced optimizer Adam with Decoupled Weight Decay Regularization (AdamW), Random Erasing (RE), and weighted loss functions, are adopted to solve issues of data unbalancing or challenging conditions like partial and occluded bodies. Experimental evaluations are performed via EPAR that contains 26 993 images of 1477 person IDs, most of which are in challenging conditions. The results show that the ConvNeXt-v2-B outperforms other networks; mean accuracy (mA) reaches 85.57%, and other indices are also the highest. The addition of AdamW or RE can improve accuracy by 1-2%. The use of new loss functions can solve the issue of data unbalancing, in which the accuracy of data-less attributes improves by a maximum of 14% in the best case. Significantly, when the attribute filtering algorithm is applied, the results are dramatically improved, and mA reaches an excellent value of 94.85%. Utilizing the state-of-the-art attribute extraction model with optimization techniques on the large-scale and diverse dataset and attribute filtering has shown a good approach and thus has a high potential for practical applications.
Dostawca treści:
Biblioteka Nauki
Artykuł

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