Miguel A. Gutiérrez-NaranjoElectronic Notes in Discrete MathematicsRocio Gonzalez-Diaz, Miguel A. Gutierrez-Naranjo, and Eduardo Paluzo-Hidalgo. Representative datasets for neural network. Electronic Notes in Discrete Mathematics, 68C:89-94, 2018....
In various examples, a generative model is used to synthesize datasets for use in training a downstream machine learning model to perform an associated task. The synthesized datasets may be generated by sampling a scene graph from a scene grammar—such as a probabilistic grammar—and applying the...
Fig. 4. Distributions of regression coefficients Rall achieved by small-dataset neural networks for surrogates (green) and real concrete data (navy) for (a) large-dataset model (1030 samples), (b) intermediate 100 sample model, and (c) small-dataset model (56 samples). (For interpretation ...
Presently, however, there are no widely accepted means for comparing the computational performance of spiking neural networks. To address this issue, we introduce a comprehensive audio-to-spiking conversion procedure and provide two novel spike-based classification datasets. The datasets are free and ...
Deep neural networks for data association in particle tracking Quantitative analysis of dynamical processes in living cells by means of fluorescence microscopy imaging requires tracking of hundreds of bright spots in n... Y Yao,I Smal,E Meijering - IEEE 被引量: 1发表: 2018年 Benchmarking robustne...
, while allowing for unconstrained information flow and/or weight sharing between analogous hidden layers of the network---thus generalising the already well-established concept of neural network ensembles (where information typically may flow only between the output layers of the individual networks). ...
A collection of datasets and neural networks for microorganism image classification. Contributers: Sari Sabban - Tarik Alafif - Abdullah Alotebi - Sally Warring - Zainab Khalifah - Stefan Geisen - Wenjia Wu Description: This is a collection of datasets and neural networks to detect or classify ...
Graph Robustness Benchmark: Rethinking and Benchmarking Adversarial Robustness of Graph Neural Networks 本文研究了图上的对抗鲁棒性问题,提供了相关的数据集,代码和leaderboard。入坑图对抗方向的同学不要错过呀~ 下图梳理了关于GNN上的对抗攻击的一系列工作: ...
What types of neural networks are commonly used for classifying network traffic? What challenges are associated with the various network traffic classification techniques? What is the primary goal of network traffic classification? What types of input data are utilized in deep learning models for networ...
ORACLE: Optimized Radio clAssification through Convolutional neuraL nEtworks L. Bertizzolo, L. Bonati, E. Demirors, T. Melodia, Arena: A 64-antenna SDR-based Ceiling Grid Testbed for Sub-6 GHz... There are more references available in the full text version of this article. ...