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Dmitry Kalenichenko
Dmitry Kalenichenko
Dirección de correo verificada de google.com
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
arXiv preprint arXiv:1704.04861, 2017
223842017
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
148222015
Quantization and training of neural networks for efficient integer-arithmetic-only inference
B Jacob, S Kligys, B Chen, M Zhu, M Tang, A Howard, H Adam, ...
Proceedings of the IEEE conference on computer vision and pattern …, 2018
27662018
Looking fast and slow: Memory-guided mobile video object detection
M Liu, M Zhu, M White, Y Li, D Kalenichenko
arXiv preprint arXiv:1903.10172, 2019
992019
Generating numeric embeddings of images
JW Philbin, GF Schroff, D Kalenichenko
US Patent 9,836,641, 2017
762017
Mnasfpn: Learning latency-aware pyramid architecture for object detection on mobile devices
B Chen, G Ghiasi, H Liu, TY Lin, D Kalenichenko, H Adam, QV Le
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020
542020
Mobilenets: Efficient convolutional neural networks for mobile vision applications
M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand
arXiv preprint arXiv: 1704.04861, 2017, 2017
512017
Mobilenets: efficient convolutional neural networks for mobile vision applications. arXiv: 170404861
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
URL http://arxiv. org/abs/1704.04861, 2017
462017
Efficient convolutional neural networks and techniques to reduce associated computational costs
AG Howard, B Chen, D Kalenichenko, TC Weyand, M Zhu, M Andreetto, ...
US Patent 11,157,814, 2021
392021
Identifying consumers in a transaction via facial recognition
S Chandrasekaran, D Kalenichenko, TR Zwiebel
US Patent 9,619,803, 2017
352017
& Adam, H.(2017)
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand
Mobilenets: Efficient convolutional neural networks for mobile vision …, 0
34
Identifying consumers via facial recognition to provide services
S Chandrasekaran, D Ho, D Kalenichenko, V Chitilian, TR Zwiebel, ...
US Patent 10,733,587, 2020
332020
Facial profile password to modify user account data for hands-free transactions
S Chandrasekaran, D Ho, D Kalenichenko, V Chitilian, TR Zwiebel, ...
US Patent 10,397,220, 2019
192019
Mobilenets: Efficient convolutional neural networks for mobile vision applications, cite
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
arXiv preprint arxiv:1704.04861 575, 2017
192017
Identifying consumers in a transaction via facial recognition
S Chandrasekaran, D Kalenichenko, TR Zwiebel
US Patent 10,726,407, 2020
182020
Facial profile modification for hands free transactions
S Chandrasekaran, D Ho, D Kalenichenko, V Chitilian, TR Zwiebel, ...
US Patent 10,482,463, 2019
162019
Mobilenets: efficient convolutional neural networks for mobile vision applications (2017). arXiv preprint
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, ...
arXiv preprint arXiv:1704.04861, 0
13
Generating object embeddings from images
GF Schroff, D Kalenichenko, K Ye
US Patent 10,657,359, 2020
52020
Memory-Guided Video Object Detection
M Zhu, M Liu, MC White, D Kalenichenko, Y Li
US Patent App. 17/432,221, 2022
22022
M.; and Adam, H. 2017. Mobilenets: Efficient convolutional neural networks for mobile vision applications
AG Howard, M Zhu, B Chen, D Kalenichenko, W Wang, TA Weyand
CoRR.[2021-05-15]. https://arxiv. org/abs/1704.04861, 0
2
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