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AlexNet
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81“... images, and the maximum Lyapunov exponents were used for prediction. GoogLeNet and ResNet-50 were used...”
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82
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83“... in comparing with GoogLeNet Inception V4 regarding several benchmarks. The experimental results indicate...”
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84“... on GoogLeNet for feature extraction, feature learning and classification. The band pass filtering is performed...”
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85
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86“... image. Face alignment is then applied to gain aligned face images as training data. We use “Goog...”
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87“... by transfer learning. AlexNet, GoogLeNet, and ResNet were used as backbone of the CNN. The best combined model...”
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88“... is the most frequently used image interpretation and classification method, including VGGNet, Goog...”
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89
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90“... of the state-of-the-art pre-trained networks: GoogLeNet, ResNet and DenseNet. We try to find the optimized deep...”
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91“...); the server side is implemented in python, and applied GoogLeNet for emotion recognition, and RNN-LSTM for Seq...”
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92“... architecture and composes each in different connection among units. Two-stream CNNs model (Goog...”
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93
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94by Wei Wang, Chengwen Zhang, Jinge Tian, Xin Wang, Jianping Ou, Jun Zhang, Ji Li“... are simpler and have fewer parameters. The experiments are compared with GoogLeNet, ResNet18, DenseNet121...”
Published 2020-01-01
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95by Fitri Damayanti“... berkembangnya dunia internet dan web maka pembuatan Sistem Informasi Rumah Kost Berbasis Web dan Googe Maps API...”
Published 2016-10-01
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96“... is modified from GoogLeNet, but has a more compact structure designed specifically for the Chinese Academy...”
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97“.... For the classification, high-level features based on Convolutional Neural Network on GoogLeNet model are used to classify...”
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98by Hakan Özcan, Bülent Gürsel Emiroğlu, Hakan Sabuncuoğlu, Selçuk Özdoğan, Ahmet Soyer, Tahsin Saygı“... learning model trained from scratch and compared the performance with pretrained AlexNet, Goog...”
Published 2021-04-01
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100by P.V. Glybochko, A.V. Lepilin, A.A. Svistunov, V.A. Bulkin, O.V. Eremin, N.V. Bulkina, L.A. Googe, D.E. SuetenkovGet full text
Published 2008-09-01
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