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Updated: Jun 29, 2025

Deep Neural Networks for Image-Based Dietary Assessment
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在贝叶斯神经网络中整合dropout和kullback-leibler调节,以改善回归中的不确定性估计

Raghavendra M Devadas1, Vani Hiremani2

  • 1Department of Computer Science and Engineering, Gitam School of Technology, GITAM (Deemed to be University), Bengaluru, India.

MethodsX
|March 29, 2024
PubMed
概括

本研究引入了一种改进的贝叶斯神经网络 (BNN) 模型,该模型增强了回归任务的不确定性预测. 新型号在准确性和可靠性方面明显优于标准BNN.

关键词:
贝叶斯神经网络是一个贝叶斯神经网络.放弃 放弃 放弃 放弃库尔巴克-莱布勒规范化的规范化机器学习是机器学习.修改后的BNN模型整合了放弃和KL规范化.回归是一种回归.不确定性量化不确定性的量化.

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