Since the emergence of Deep Neural Networks (DNNs) as a prominent technique in the field of computer vision, the ImageNet classification challenge has played a major role in advancing the state-of-the-art. While accuracy figures have steadily increased, the resource utilisation of winning models ...
论文笔记-An Analysis of Deep Neural Network Models for Practical Applications https://arxiv.org/abs/1605.07678 摘要 本文全面分析了在实际应用中的几项重要指标:准确率、内存占用、参数、操作数量、推理时间、功耗,并得出了以下几项主要研究结论: (1)功耗与batch size和网络架构无关; (2)准确率和推理时间...
we provide a unification, comparison, and analysis of existing explainability approaches for DNNs across various applications and input domains. we present and discuss the results of a Mechanical Turk study identifying the relative preference of explanation styles by an average non-technical end-user. ...
Analysis of Deep Convolutional Neural Network Architectures To improve deep learning architectures an analysis is given of the ac- tivation values in four different architectures using various activation functions. Current state of the art classifiers use dropout, max-pooling as well as the ... JV ...
Fig. 1. Diagram of Deep Neural Network. For binary classification, there is only one output Y that is the class probability or class label. Since the transformation from class probability to class label is straightforward, we focus on the case where the output is the class probability. The ...
[54]Aladin Virmaux and Kevin Scaman. Lipschitz regularity of deep neural networks: analysis and efficient estimation. InNeurIPS, pages 3839–3848, 2018. [55]Nikil Wale, Ian A Watson, and George Karypis. Comparison of descriptor spaces for chemical compound retrieval and classification.Knowledge and...
The recent increase in both dataset sizes and computing power have allowed the application of Convolutional Neural Networks (CNNs) to the specific case of image analysis, which apply convolutions on the input image. CNNs are the most commonly used deep network, and they are trained on either ...
pythonmachine-learningdeep-neural-networksdeep-learningneural-networktensorflowmldistributed Resources Readme License Apache-2.0 license Code of conduct Code of conduct Security policy Security policy Citation Cite this repository Activity Custom properties ...
The authors shall review these models within a common framework and explore their connections, and shall also review the recent developments that take advantage of the high approximation capacities of deep neural networks. From information scaling of natural images to regimes of statistical models - ...
An Empirical Study of Example Forgetting During Deep Neural Network Learning 论文理解 corazju 躺平大魔王18 人赞同了该文章 今天给大家分享一篇ICLR 19上的一片有关神经网络遗忘的论文,虽然时间比较久了,但是这片论文和现在大火的unlearning,meta-learning比较相关,也跟我自己的研究方向比较接近,希望能给大家一些有...