Going Deeper With Convolutions - Google Scholar Metrics

Articles citing Going Deeper With Convolutions

Title / Author	Year
Imagenet classification with deep convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton Advances in neural information processing systems, 1097-1105	2012
Deep residual learning for image recognition K He, X Zhang, S Ren, J Sun Proceedings of the IEEE conference on computer vision and pattern …	2016
Very deep convolutional networks for large-scale image recognition K Simonyan, A Zisserman arXiv preprint arXiv:1409.1556	2014
Data mining: practical machine learning tools and techniques with Java implementations IH Witten, E Frank Acm Sigmod Record 31 (1), 76-77	2002
Deep learning Y LeCun, Y Bengio, G Hinton nature 521 (7553), 436-444	2015
Faster r-cnn: Towards real-time object detection with region proposal networks S Ren, K He, R Girshick, J Sun Advances in neural information processing systems, 91-99	2015
Batch normalization: Accelerating deep network training by reducing internal covariate shift S Ioffe, C Szegedy arXiv preprint arXiv:1502.03167	2015
Imagenet large scale visual recognition challenge O Russakovsky, J Deng, H Su, J Krause, S Satheesh, S Ma, Z Huang, ... International journal of computer vision 115 (3), 211-252	2015
Deep learning I Goodfellow, Y Bengio, A Courville MIT press	2016
Fully convolutional networks for semantic segmentation J Long, E Shelhamer, T Darrell Proceedings of the IEEE conference on computer vision and pattern …	2015
You only look once: Unified, real-time object detection J Redmon, S Divvala, R Girshick, A Farhadi Proceedings of the IEEE conference on computer vision and pattern …	2016
Densely connected convolutional networks G Huang, Z Liu, L Van Der Maaten, KQ Weinberger Proceedings of the IEEE conference on computer vision and pattern …	2017
Deep learning in neural networks: An overview J Schmidhuber Neural networks 61, 85-117	2015
Ssd: Single shot multibox detector W Liu, D Anguelov, D Erhan, C Szegedy, S Reed, CY Fu, AC Berg European conference on computer vision, 21-37	2016
Tensorflow: A system for large-scale machine learning M Abadi, P Barham, J Chen, Z Chen, A Davis, J Dean, M Devin, ... 12th {USENIX} symposium on operating systems design and implementation …	2016
Rethinking the inception architecture for computer vision C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna Proceedings of the IEEE conference on computer vision and pattern …	2016
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification K He, X Zhang, S Ren, J Sun Proceedings of the IEEE international conference on computer vision, 1026-1034	2015
Facenet: A unified embedding for face recognition and clustering F Schroff, D Kalenichenko, J Philbin Proceedings of the IEEE conference on computer vision and pattern …	2015
Show, attend and tell: Neural image caption generation with visual attention K Xu, J Ba, R Kiros, K Cho, A Courville, R Salakhudinov, R Zemel, ... International conference on machine learning, 2048-2057	2015
Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs LC Chen, G Papandreou, I Kokkinos, K Murphy, AL Yuille IEEE transactions on pattern analysis and machine intelligence 40 (4), 834-848	2017

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