Information about Test

  1. Feature learning

    aimlexchange.com/search/wiki/page/Feature_learning

    are learned using labeled input data. Examples include supervised neural networks, multilayer perceptron and (supervised) dictionary learning. In unsupervised

  2. Attention

    aimlexchange.com/search/wiki/page/Attention

    Q, Hua G, Zheng N (2018). "Attention-Based Temporal Weighted Convolutional Neural Network for Action Recognition". IFIP Advances in Information and Communication

  3. CIFAR-10

    aimlexchange.com/search/wiki/page/CIFAR-10

    try different algorithms to see what works. Various kinds of convolutional neural networks tend to be the best at recognizing the images in CIFAR-10. CIFAR-10

  4. Recursive neural network

    aimlexchange.com/search/wiki/page/Recursive_neural_network

    include Graph Neural Network (GNN), Neural Network for Graphs (NN4G), and more recently convolutional neural networks for graphs. Goller, C.; Küchler, A

  5. Google Translate

    aimlexchange.com/search/wiki/page/Google_Translate

    languages, with the release of a new implementation that utilizes convolutional neural networks, and also enhanced the speed and quality of Conversation Mode

  6. Long short-term memory

    aimlexchange.com/search/wiki/page/Long_short-term_memory

    artificial recurrent neural network (RNN) architecture used in the field of deep learning. Unlike standard feedforward neural networks, LSTM has feedback

  7. Deep Image Prior

    aimlexchange.com/search/wiki/page/Deep_Image_Prior

    type of convolutional neural network used to enhance a given image with no prior training data other than the image itself. A neural network is randomly

  8. Yann LeCun

    aimlexchange.com/search/wiki/page/Yann_LeCun

    recognition and computer vision using convolutional neural networks (CNN), and is a founding father of convolutional nets. He is also one of the main creators

  9. Support vector machine

    aimlexchange.com/search/wiki/page/Support_vector_machine

    for Multiclass Support Vector Machines" (PDF). IEEE Transactions on Neural Networks. 13 (2): 415–25. doi:10.1109/72.991427. PMID 18244442. Platt, John;

  10. SpaCy

    aimlexchange.com/search/wiki/page/SpaCy

    learning library Thinc. Using Thinc as its backend, spaCy features convolutional neural network models for part-of-speech tagging, dependency parsing, text categorization

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