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2019/09/02
Yuji Yamamoto (@y_yammt)
WWW2019 

(@CyberAgent, Inc.)
• Research track: Mobile and Ubiquitous Computing
• ( )
:
• (Android) DeepLearning
?
2
Research track: Mobile and Ubiquitous
Computing
Research track: Mobile and Ubiquitous Computing
• Web of Things, Ubiquitous and Mobile Computing
CFP
• :
• ( )
•
• …
•
^^;...
•
1. CBHE: Corner-based Building Height Estimation for Complex Street Scene Images
2. STFNets: Learning Sensing Signals fr...
(1/2)
• CBHE: Corner-based Building Height Estimation for Complex Street Scene Images
• 2D
( )
• STFNets: Learning Sensing...
(2/2)
• Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction
• (
)
• Cookie Synchroniza...
A First Look at Deep Learning Apps

on Smartphones
•
• Android 

Deep Learning
• Google Play 2018/07 2018/09 

16,500
•
9
: https://github.com/xumengwei/MobileDL
10
: DL Android
• Google Play 16,500
• 2018/06 DL 166
• 2018/09 DL 211
• 1.3% 11.9%
10.5%
• DL Google LLC (10), Fotoable, Inc...
: DL ?
• 2018/09 211 DL
DL
• 1 2
•
• (97), (52)
12
: DL ?
13
• TensorFlow, TFLite, ncnn
• DL Parrots
OSS
•
• Parrots SenseTime DL
• 2018/06, 09 ncnn, TFLite
• , 

?
: DL ?
14
• 71 DL 176 DL
• 98
• 78.8% CNN 7.8% RNN
• CNN: / ,
• RNN: /
• NN
• 1 softmax 1
: DL (1/2)
• DL
• ( / )
•
• 2
• :
• :
15
: DL (2/2)
• TensorFlow, TFLite, ncnn, caffe, Caffe2 120 DL
• 47 (39.2%) 23(19.2%)
• → …
• DL
• (ncnn )
•
• → OS/ ?
16
• Research track: Mobile and Ubiquitous Computing
• Android DeepLearning
• WWW Web
•
18
WWW2019で見るモバイルコンピューティングの技術と動向    山本悠ニ
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WWW2019で見るモバイルコンピューティングの技術と動向 山本悠ニ

  1. 1. 2019/09/02 Yuji Yamamoto (@y_yammt) WWW2019 
 (@CyberAgent, Inc.)
  2. 2. • Research track: Mobile and Ubiquitous Computing • ( ) : • (Android) DeepLearning ? 2
  3. 3. Research track: Mobile and Ubiquitous Computing
  4. 4. Research track: Mobile and Ubiquitous Computing • Web of Things, Ubiquitous and Mobile Computing CFP • : • ( ) • • … • ^^; 4
  5. 5. • 1. CBHE: Corner-based Building Height Estimation for Complex Street Scene Images 2. STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short-Time Fourier Neural Networks 3. Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction • 4. A First Look at Deep Learning Apps on Smartphones ( ) 5. Cookie Synchronization: Everything You Always Wanted to Know But Were Afraid to Ask 5
  6. 6. (1/2) • CBHE: Corner-based Building Height Estimation for Complex Street Scene Images • 2D ( ) • STFNets: Learning Sensing Signals from the Time-Frequency Perspective with Short- Time Fourier Neural Networks • IoT Deep Learning NN Short-Time Fourier Neural Network (STFNet) 6
  7. 7. (2/2) • Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction • ( ) • Cookie Synchronization: Everything You Always Wanted to Know But Were Afraid to Ask • Cookie Sync (DSP SSP DMP ID ) 850 Web Cookie Sync 7
  8. 8. A First Look at Deep Learning Apps
 on Smartphones
  9. 9. • • Android 
 Deep Learning • Google Play 2018/07 2018/09 
 16,500 • 9
  10. 10. : https://github.com/xumengwei/MobileDL 10
  11. 11. : DL Android • Google Play 16,500 • 2018/06 DL 166 • 2018/09 DL 211 • 1.3% 11.9% 10.5% • DL Google LLC (10), Fotoable, Inc (6)
 2 DL Adobe, Facebook, Kakao, Meitu 11
  12. 12. : DL ? • 2018/09 211 DL DL • 1 2 • • (97), (52) 12
  13. 13. : DL ? 13 • TensorFlow, TFLite, ncnn • DL Parrots OSS • • Parrots SenseTime DL • 2018/06, 09 ncnn, TFLite • , 
 ?
  14. 14. : DL ? 14 • 71 DL 176 DL • 98 • 78.8% CNN 7.8% RNN • CNN: / , • RNN: / • NN • 1 softmax 1
  15. 15. : DL (1/2) • DL • ( / ) • • 2 • : • : 15
  16. 16. : DL (2/2) • TensorFlow, TFLite, ncnn, caffe, Caffe2 120 DL • 47 (39.2%) 23(19.2%) • → … • DL • (ncnn ) • • → OS/ ? 16
  17. 17. • Research track: Mobile and Ubiquitous Computing • Android DeepLearning • WWW Web • 18
  • mgoldchild

    May. 20, 2021
  • syuichitsuji

    Sep. 10, 2019

WWW2019で見るモバイルコンピューティングの技術と動向 山本悠ニ

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