Examples of using Convolutional in English and their translations into Ukrainian
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Convolutional Neural Networks.
Caffe: A library for convolutional neural networks.
Convolutional Neural Networks.
Depth/ 3D extraction using convolutional neural networks;
Convolutional neural networks that learn….
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Like many Google technologies, PoseNet is powered by a convolutional neural network.
Convolutional Neural Networks(CNNs) have been used to….
The new technology is based on the convolutional neural network(CNN) consisting of two parts.
Convolutional deep neural networks(CNNs) are used in computer vision.
Like many other Google Research breakthroughs, this one used a convolutional neural network.
In 1955, he introduced convolutional codes as an alternative to block codes.
The algorithm described in the pages of JAMA Opthalmology, works on the principle of convolutional neural networks.
An expert in deep convolutional neural networks and their application in the computer vision.
Classification technology detects every incoming document type, including images,by using deep learning Convolutional Neural Networks and sorts documents by appearance or pattern;
That performance of convolutional neural networks on the ImageNet tests was close to that of humans.
This input data is then transmitted through convolutional layers, in which not all nodes are interconnected.
Convolutional neural networks usually require a large amount of training data in order to avoid overfitting.
A parameter sharing scheme is used in convolutional layers to control the number of free parameters.
Convolutional neural networks(CNN or deep convolutional neural networks, DCNN) are quite different from most other networks.
CDBNs have structure very similar to a convolutional neural networks and are trained similar to deep belief networks.
This allows convolutional networks to be successfully applied to problems with small training sets.
Linear codes are traditionally partitioned into block codes and convolutional codes, although turbo codes can be seen as a hybrid of these two types.
Fundamentally, convolutional codes do not offer more protection against noise than an equivalent block code.
Today, deep neural networks with different architectures, such as convolutional, recurrent and autoencoder networks, are becoming an increasingly popular area of research.
A Simple Convolutional Neural Network for Recognition of Handwritten Digits// The Tenth All-Ukrainian International Conference on Signal/Image Processing and Pattern Recognition UkrObraz'2010.
The report is devoted to the use of convolutional networks in order to create real-time computer systems for flame detection.
Finally, after several convolutional and max pooling layers, the high-level reasoning in the neural network is done via fully connected layers.
Technically it uses deep learning on a convolutional neural network, with a novel form of Q-learning, a form of model-free reinforcement learning.
A new method based on convolutional neural networks, when testing showed 98% accuracy in the diagnosis of abnormalities and surpassed in this professional ophthalmologists.
The algorithm for convolutional neural networks was previously used by Google and Facebook to recognize images in photos, and Tesla used it to create unmanned vehicles.