Examples of using Dnn in English and their translations into Vietnamese
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CMS with DotNetNuke(DNN).
O Scaling up/out and speedup DNN training and decoding;
The future is bright for DNN!
Since DNN is not centralized, it does not suffer from having a single point of failure.
I am certainly not an expert on DNN.
ERR Dnn","ERR Enn": A problem during data copying(e.g. the USB drive disconnected during data copying).
Give me fuel, give me fire, give me DNN that I desire.
DNN is currently in its alpha stage and features basic functionality for writers, reviewers, and readers.
Along with submitting a story for review,the writer will pay a fee in DNN tokens;
Copty and his colleagues trained a DNN model on the data that they had previously generated.
DNN prediction is very fast and it is thought that DNNs do not require any feature extraction at all.".
There are four community roles in the DNN ecosystem: writers, reviewers, readers, and publishers.
DNN will harness the power of the Ethereum blockchain to create an infrastructure that is virtually impossible to infiltrate or take down.
Despite many similarities to‘ecosystemic' platforms such as Civil and DNN, PUBLIQ has a number of distinctive features.
DNN harnesses the power of the Ethereum blockchain to allow for a fully decentralized network that can never be hacked into, taken down, or censored.
A DBN can be used to generatively pre-train a DNN by using the learned DBN weights as the initial DNN weights.
CyStack research showed that 70 per cent of the attacks were targeted at websites using popular open source WordPress CMS(content management system),followed by Joomla and DNN.
There are many training parameters to be considered with a DNN, such as the size(number of layers and number of units per layer), the learning rate and initial weights.
DNN, or Decentralized News Network, is a news platform, combining news creation with decentralized networks to deliver factual content, curated by the community.
By 2023, it's expected that new special-purpose chips will reduce the power consumption required to run a DNN, enabling new edge architectures and embedded DNN functions in low-power IoT endpoints.
Unlike Civil and DNN, Media Sifter's main focus is not on production of the original news but rather on community validation and investigation of the outside content.
Working experiences: Having over 16-year-working experience of developing and building up brand name for some big companies and corporations in Vietnam andcurrently being general director of DNN Motorbike Accessories Corporation.
New journalistic enterprises such as Civil, DNN, and MediaSifter are putting up architectures that aim at fixing the broken news by using brand new incentive systems and collaborative fact-checking.
These logic networks are then capable of dealing with very large data sets and identify and classify information with high probability and accuracy at very high speed,yet improve their DNN as they keep learning and sifting through data.
In 2010, the DNN Company contributed VND 80 million to the“Understanding the Heart” program by purchasing 800“Understanding the heart” books in the launching ceremony of the“Understanding the Heart” Charity Association in Ho Chi Minh City.
By training the neural networks on radar and lidar data instead of relying on the flat ground assumption,we enable the DNN to estimate distance to objects from a single camera, even when the vehicle is going up or down hill.
Training a DNN network involves exposing it to a massive collection of examples, each time tweaking the way in which the neurons are connected so that, eventually, the top layer gives the desired answer- such as always interpreting a picture of a lion as a lion, even if the DNN hasn't seen that picture before.
Method PER(%) Randomly Initialized RNN 26.1 Bayesian Triphone GMM-HMM 25.6 Hidden Trajectory(Generative) Model 24.8 Monophone Randomly Initialized DNN 23.4 Monophone DBN-DNN 22.4 Triphone GMM-HMM with BMMI Training 21.7 Monophone DBN-DNN on fbank 20.7 Convolutional DNN[168] 20.0 Convolutional DNN w.
Such analysis on TIMIT by Li Deng and collaborators around 2009-2010,contrasting the GMM(and other generative models of speech) vs. DNN models, stimulated early industrial investment in deep learning for speech recognition from small to large scales,[36][47] eventually leading to pervasive and dominant use in that industry.