Examples of 'cnns' in a sentence
Meaning of "cnns"
cnns (noun): Acronym for Cable News Network, a U.S.-based news television channel. It is widely known for its news coverage and programming
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- plural of CNN
How to use "cnns" in a sentence
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cnns
Build an image classification model with CNNs.
Broader applications of CNNs include video and speech recognition.
Cnns great big story.
Another power tool that CNNs use is called pooling.
The method may be more verifiable than traditional CNNs.
It significantly improved the accuracy of CNNs when they had few layers.
Build a hybrid model using object detection architectures and CNNs.
This second study shows the relevance of using CNNs for measuring displacement and deformation fields.
CNNs are often used in image recognition systems.
Here are two tutorials on how to build CNNs from scratch.
LSTM combined with CNNs improved automatic image captioning.
Through the use of wireless detection techniques the output throughput of CNNs is drastically increased.
CNNs use a variation of multilayer perceptrons designed to require minimal preprocessing.
For multiple plane CNNs there needs be only one GAPU.
CNNs have also been explored for natural language processing.
See also
Our proposed methods are suitable for using shallow CNNs for multimodal MRI images.
CNNs are of major interest in the application of computer vision techniques in remote sensing.
In the world of neural networks, CNNs are widely used for image classification.
CNNs give better results but their performances are not sufficient for industrial use.
These systems share building blocks, gated RNNs and CNNs and trained attention mechanisms.
And if the CNNs and the Foxes and the CNBCs are not buying.
Subsequently, we proposed a new usage of CNNs for the SRE problem.
LSTM combined with CNNs also improved automatic image captioning and a plethora of other applications.
It 's inspired by the CNNs.
CNNs use various types of regularization.
This architecture allows CNNs to take advantage of the 2D structure of input data.
CNNs compare images piece by piece.
Another important concept of CNNs is pooling, which is a form of non-linear down-sampling.
CNNs use more hyperparameters than a standard multilayer perceptron MLP.
Since 2011, fast implementations of CNNs on GPUs have won many visual pattern recognition competitions.
CNNs Christiane Amanpour says she is undergoing treatment for ovarian cancer.
As opposed to MLPs, CNNs have the following distinguishing features, 3D volumes of neurons.
CNNs are suitable for processing visual and other two-dimensional data.
ImageNet-trained CNNs are biased towards texture ; increasing shape bias improves accuracy and robustness.
CNNs use relatively little pre-processing compared to other image classification algorithms.
CNNs apply to image processing, natural language processing and other kinds of cognitive tasks.
CNNs eliminate the need for manual feature extraction-the features are learned directly by the CNN.
