atrous

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English

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Etymology 1

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From Latin āter (dark, black) +‎ -ous.

Pronunciation

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Adjective

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atrous (comparative more atrous, superlative most atrous)

  1. jet-black in color.
    • 1830, Jonathan Stokes, Botanical Commentaries- Volume 1:
      Male atrous leadcolourd[sic] on the upper side, under side a mixture of whitish and ferruginous with cuspidate fasciae ;
    • 1917, Proceedings of the Linnean Society of New South Wales:
      Head atrous, viridescent on lateral frontal spaces and occiput, gulae, basal part of mentum on each side of median tooth brightly viridescent; prothorax atrous, with viridescent tints on disc and wide brassy-green basal and lateral margins.
    • 1968, Iconographia Mycologica - Issues 22-27:
      Perithecia sparse, innate, then erumpent for apical portion, subglobose, atrous, with ostiollar portion a little enlarged.
    • 2013, DB Angel, The Gift, page 13:
      An imposing portrait of a Caucasian male holding an atrous book with a sheepish smile hung ominously over the bed.
    • 2014, Mark Alan Lindsley, Future Earth, page 405:
      The throng shouted, female Eligor flung flowers from the roofs as the rhythmic chiming of iron-shod riding beasts came clearer, and the first of the mighty array swung into view in the broad, atrous streets that curved round the spired Grand Union of Imperial Opal.
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Etymology 2

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From French à trous (with holes).

Pronunciation

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Adjective

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atrous (not comparable)

  1. (computing, uncommon) dilated (used when describing convolutions) [1]
    Atrous convolution allows us to explicitly control the resolution.
    • 2008, Sharon Priya, A. Srinivasan, “Image and Video Denoising by Sparse 3-D Transform Domain Using Atrous and Gabor Wavelets”, in Proceedings Second International Conference on Information Processing, page 87:
      The new approach is executed by using atrous and gabor wavelets that work effectively on image and video.
    • 2019, Qi Wang, Learning to Understand Remote Sensing Images, page 158:
      In order to further illustrate the effect of "atrous" convolution, we compare it with standard convolution using a simple example in Figure 4.
    • 2019, Guanhong Zhang, Muyi Sun, Xiaoguang Zhou, “Sub-pixel Upsampling Decode Network for Semantic Segmentation”, in Artificial Intelligence, page 18:
      As the frameworks based on atrous convolution and ASPP module have proved their success, we implement an encoder with similar structure of [5], using a pretrained ResNetV2 as backbone network.

Anagrams

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