[1] |
黄永安, 熊蔡华, 熊有伦 . 智能机器人与应用的现状与发展趋势[J]. 国际学术动态, 2009: 38-39.
|
|
HUANG Y A , XIONG C H , XIONG Y L . Status and development trend of intelligent robots and applications[J]. International Academic Developments, 2009: 38-39.
|
[2] |
徐扬生 . 智能机器人引领高新技术发展[J]. 企业科协, 2010(9): 28-31.
|
|
XU Y S . Intelligent robots lead high-tech development[J]. Enterprise Association, 2010(9): 28-31.
|
[3] |
谭民, 王硕 . 机器人技术研究进展[J]. 自动化学报, 2013,39(7): 963-972.
|
|
TAN M , WANG S . Research progress on robotics[J]. Acta Automatica Sinica, 2013,39(7): 963-972.
|
[4] |
HE J X , BAXTER S L , XU J ,et al. The practical implementation of artificial intelligence technologies in medicine[J]. Nature Medicine, 2019: 30-36.
|
[5] |
TAIGMAN Y , YANG M , RANZATO M ,et al. DeepFace:closing the gap to human-level performance in face verification[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2014.
|
[6] |
SUN Y , WANG X , TANG X . Deep learning face representation from predicting 10000 classes[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2014.
|
[7] |
PARKHI O M , VEDALDI A , ZISSERMAN A ,et al. Deep face recognition[C]// Proceedings of the British Machine Vision Conference.[S.l.:s.n.], 2015.
|
[8] |
SCHROFF F , KALENICHENKO D , PHILBIN J . FaceNet:a unified embedding for face recognition and clustering[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2015.
|
[9] |
DENG J , GUO J , ZAFEIRIOUS S . ArcFace:additive angular margin loss for deep face recognition[J]. arXiv preprint,2018,arXiv:1801.07698.
|
[10] |
CHEN D , CAO X , WANG L ,et al. Bayesian face revisited:a joint formulation[C]// Proceedings of the 12th European Conference on Computer Vision-Volume Part III. Berlin:Springer, 2012: 566-579.
|
[11] |
SANKARANARAYANAN S , ALAVI A , CHELLAPPA R . Triplet similarity embedding for face verification[J]. arXiv preprint,2016,arXiv:1602.03418.
|
[12] |
SANKARANARAYANAN S , ALAVI A , CASTILLO C D ,et al. Triplet probabilistic embedding for face verification and clustering[C]// Proceedings of the 2016 IEEE 8th International Conference on Biometrics Theory,Applications and Systems. Piscataway:IEEE Press, 2016.
|
[13] |
KUMARB G V , CARNEIRO G , REID I . Learning local image descriptors with deep Siamese and triplet convolutional networks by minimizing global loss functions[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. Piscataway:IEEE Press, 2016.
|
[14] |
TRIGUEROS D S , MENG L , HARTNETT M . Enhancing convolutional neural networks for face recognition with occlusion maps and batch triplet loss[J]. Image and Vision Computing, 2017(79).
|
[15] |
SABOUR S , FROSST N , HINTON G E . Dynamic routing between capsules[C]// Proceedings of the 31st Conference and Workshop on Neural Information Processing Systems.[S.l.:s.n.], 2017.
|
[16] |
ZHANG C , LI H , CHEN C ,et al. Enhanced group sparse regularized nonconvex regression for face recognition[C]// Proceedings of the IEEE Transactions on Pattern Analysis and Machine Intelligence. Piscataway:IEEE Press, 2020.
|
[17] |
ELMAHMUDI A , UGAIL H . Deep face recognition using imperfect facial data[J]. Future Generation Computer Systems, 2019,99: 213-225.
|
[18] |
DAHLG E , YU D , DENG L ,et al. Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition[J]. IEEE Transactions on Audio,Speech,and Language Processing, 2011,20(1): 30-42.
|
[19] |
VINYALS O , RAVURI S V , POVEY D . Revisiting recurrent neural network for robust ASR[C]// Proceedings of the 37th International Conference on Acoustics,Speech and Signal Processing. Piscataway:IEEE Press, 2012.
|
[20] |
MAAS A L , LE Q V , O’NEIL T M ,et al. Recurrent neural networks for noise reduction in robust ASR[C]// Proceedings of the INTERSPEECH. Piscataway:IEEE Press, 2012.
|
[21] |
GRAVESA , JAITLY N , MOHAMED A R . Hybrid speech recognition with deep bidirectional LSTM[C]// Proceedings of the 2013 IEEE Workshop on Automatic Speech Recognition and Understanding. Piscataway:IEEE Press, 2013.
|
[22] |
ABDEL-HAMID O , MOHAMED A , JIANG H ,et al. Convolutional neural networks for speech recognition[J]. IEEE Transactions on Audio,Speech,and Language Processing, 2014,22(10): 1533-1545.
|
[23] |
SAINATH T N , VINYALS O , SAK H . Convolutional,long short-term memory,fully connected deep neural networks[C]// Proceedings of the 40th IEEE International Conference on Acoustics,Speech and Signal Processing. Piscataway:IEEE Press, 2015.
|
[24] |
GRAVES A , FERNANDEZ S , GOMEZ F ,et al. Connectionist temporal classification:labelling unsegmented sequence data with recurrent neural networks[C]// Proceedings of the 23rd International Conference on Machine Learning.[S.l.:s.n.], 2006: 25-29.
|
[25] |
HANNUN A , CASE C , CASPER J ,et al. Deep Speech:scaling up end-to-end speech recognition[J]. arXiv preprint,2014,arXiv:1412.5567.
|
[26] |
AMODEI D , ANANTHANARAYANAN S , ANUBHAI R ,et al. Deep Speech 2:end-to-end speech recognition in English and Mandarin[C]// Proceedings of the 33rd International Conference on |