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请输入英文单字，中文词皆可：

pooling    音标拼音: [p'ulɪŋ]
adj. 共用的

共用的

Pooling \Pool"ing\, n. (Law)
The act of uniting, or an agreement to unite, an aggregation
of properties belonging to different persons, with a view to
common liabilities or profits.
[1913 Webster]


Pool \Pool\, v. t. [imp. & p. p. {Pooled}; p. pr. & vb. n.
{Pooling}.]
To put together; to contribute to a common fund, on the basis
of a mutual division of profits or losses; to make a common
interest of; as, the companies pooled their traffic.
[1913 Webster]

Finally, it favors the poolingof all issues. --U. S.
Grant.
[1913 Webster]

69 Moby Thesaurus words for "pooling":
bipartisanship, centering, centralism, centralization, coaction,
coadjuvancy, coadministration, coagency, cochairmanship,
codirectorship, collaboration, collaborativeness, collectivism,
collusion, commensalism, common effort, common enterprise,
communalism, communism, communitarianism, community, complicity,
concentralization, concentration, concert, concord, concordance,
concurrence, convergence, cooperation, cooperativeness, duet,
duumvirate, ecumenicalism, ecumenicism, ecumenism, esprit,
esprit de corps, fellow feeling, fellowship, focalization,
focusing, harmony, joining of forces, joint effort,
joint operation, mass action, morale, mutual assistance, mutualism,
mutuality, octet, pooling of resources, pulling together, quartet,
quintet, reciprocity, septet, sextet, solidarity, symbiosis,
synergism, synergy, team spirit, teamwork, trio, triumvirate,
troika, united action


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  • CNN | Introduction to Pooling Layer - GeeksforGeeks
    Pooling layer is used in CNNs to reduce the spatial dimensions (width and height) of the input feature maps while retaining the most important information It involves sliding a two-dimensional filter over each channel of a feature map and summarizing the features within the region covered by the filter
  • Pooling and their types in CNN - Medium
    Pooling, also known as subsampling or downsampling, is a technique used in CNNs to reduce the spatial dimensions of feature maps while retaining essential information
  • Neural Networks: Pooling Layers | Baeldung on Computer Science
    In this tutorial, we’ll walk through pooling, a machine-learning technique widely used that reduces the size of the input and, thus the complexity of deep learning models while preserving important features and relationships in the input data
  • POOLING | English meaning - Cambridge Dictionary
    POOLING definition: 1 the act of sharing or combining two or more things: 2 a method of accounting used when two… Learn more
  • What is Pooling Operation? - GeeksforGeeks
    Pooling is a technique used in CNNs to reduce the spatial dimensions (width and height) of input feature maps It involves aggregating information from nearby pixels into a single representative value, typically by selecting the maximum value or computing the average
  • What is Pooling? Definition, Types, Benefits and Examples | Logos Logistics
    In logistics, "pooling" is like teamwork for transporting and storing goods It involves combining shipments, inventories, or resources from different sources into one efficient move This strategy helps save money, improve service, and reduce environmental impact
  • 7. 5. Pooling — Dive into Deep Learning 1. 0. 3 documentation - D2L
    Like convolutional layers, pooling operators consist of a fixed-shape window that is slid over all regions in the input according to its stride, computing a single output for each location traversed by the fixed-shape window (sometimes known as the pooling window)
  • Everything about Pooling layers and different types of Pooling
    We have explored the idea and computation details behind pooling layers in Machine Learning models and different types of pooling operations as well In short, the different types of pooling operations are Maximum Pool, Minimum Pool, Average Pool and Adaptive Pool
  • Pooling
    Pooling: Overview After obtaining features using convolution, we would next like to use them for classification In theory, one could use all the extracted features with a classifier such as a softmax classifier, but this can be computationally challenging
  • Pooling (Machine Learning) - Deepgram
    Pooling in machine learning simplifies the complex structures of data by reducing their dimensions, which, in turn, enhances the computational efficiency of models, especially in tasks involving high-dimensional inputs like images or videos





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