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  • 深度自适应动态神经网络进展综述 - Researching
    深度神经网络（DNN）极大地推动了人工智能技 术的进步。DNN 依靠级联非线性计算单元[1]和过参 数化[2-3]等先验获得了比传统机器学习算法更强的非 线性特征表征能力和基于隐式约束的可优化能力。以 AlexNet[4]、ResNet[5]、VGG[6]为代表的神经网络结构
  • U. S. DEP ARTMENT OF U S DEPARTMENT OF ENERGY DOE ENERGY . . .
    efforts to achieve our nonproliferation goals at home and abroad DNN staff have shown incredible tenacity, innovation, and commitment to their work as we continue maneuvering through this unique work environment I am proud of DNN’s wide range of contributions to our national security, and truly grateful to serve alongside such a talented team
  • 基于可解释性分析的深度神经网络优化方法
    训练dnn，以提升模型性能达到优化dnn的目的 在使用3个数据集训练的9个dnn模型上的实验结 果表明，optdia可以将dnn的准确率提升0 39~2 15个百分点，f1-score提升0 11~2 03个百分点 关键词 深度神经网络；dnn优化；dnn缺陷；dnn性能；可解释性分析 中图法分类号 tp311 5
  • Discovering and Explaining the - ICLR
    an entire complex DNN • A single scalar metric cannot reflect the diversity of reasons that contribute to the performance of an entire complex DNN Output of DNN The DNN encodes diverse and complex logic among patches Input … insert insert insert insert • Accuracy • Loss • Adversarial accuracy • … cannot reflect
  • GAO-17-210, NUCLEAR NONPROLIFERATION: Better Information . . .
    Specifically, the DNN Research and Development (DNN R D) and Nonproliferation and Arms Control (NPAC) programs track and document technology advancements resulting from their projects, such as in project reports However, NNSA officials acknowledged that DNN R D—by far the larger program—does not consistently track and
  • 基于DNN 特征融合的噪声鲁棒性语音识别*
    练一个结构稍浅的dnn。 图2 隐藏层融合实现框架图 2 3 输出层融合 dnn 输出层融合是对dnn 输出状态的后验 概率特征进行拼接，然后训练一个mlp，利用融 合得到的后验概率特征解码进行识别，图3 是输 出层融合的实现框架图，需要在已有dnn 基础 上额外训练一个mlp。
  • U. S. DEP ARTMENT OF U S ENERGY NATIONAL DEFENSE DNN NN Sentinel
    DNN has risen to the challenge of incorporating the fast-paced emergence of technological capabilities into the way we approach our mission Over the past fifteen years DNN’s R D program, for example, has seen exponential growth, evolving from a “hobby shop” with small individual projects to a much larger





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