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Updated: Jul 29, 2025

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在复杂的背景下使用MC-SCMNet对狗便进行细粒度图像分类方法

Jinyu Liang1, Weiwei Cai2, Zhuonong Xu1

  • 1College of Computer & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China.

Animals : an open access journal from MDPI
|May 27, 2023
PubMed
概括

这项研究介绍了MC-SCMNet,这是一种用于准确识别狗便的新型深度学习模型. 它有效地处理复杂的背景和环境退化,实现犬类健康监测的高精度.

关键词:
复杂的背景 复杂的背景深度学习是一种深度学习.这些狗狗狗狗狗狗狗狗.便识别 便识别 便识别细粒度图像的分类细粒度图像的分类胃肠道的监测 胃肠道的监测

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In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
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