mạng neuron - mica.edu.vn
TRANSCRIPT
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International Research Institute MICAMultimedia, Information, Communication & Applications
UMI 2954
Hanoi University of Science and Technology
1 Dai Co Viet - Hanoi - Vietnam
Mạng neuron
và ứng dụng trong xử lý tín hiệu
Mạng neuron
và ứng dụng trong xử lý tín hiệu
Giảng viên
Trần Thị Thanh Hải
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Bài 10:
Mạng neuron sâu
(Deep neural network)
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Giới thiệu
Source: Introduction to Deep Learning MIT 6.S191
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Deep and shallow network
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Why? –Achieved State of the Art in a Number of Different Areas
Language Modeling (2012, Mikolov et al)
Image Recognition (Krizhevsky won 2012 ImageNet competition)
Sentiment Classification (2011, Socher et al)
Speech Recognition (2010, Dahl et al)
MNIST hand-written digit recognition (Ciresan et al, 2010)
Andrew Ng – Machine Learning Professor, Stanford:
“I’ve worked all my life in Machine Learning, and I’ve never seen one algorithm knock over benchmarks like Deep Learning”
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Một số kiến trúc mạng neuron sâu (tích chập)
ứng dụng trong các bài toán phân tích nhận
dạng ảnh và video
=> sẽ được trình bày vào tuần sau
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Bài 11:
Mạng neuron tích chập
(Convolutional Neural
Network)
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Giới thiệu chung
Mạng neuron tích chập đang là một tiến hóa lớn, có tầm
ảnh hưởng trong lĩnh vực về thị giác máy tính
2012 là năm đầu tiên Alex Krizhevsky đã ứng dụng
mạng neuron tích chập và thắng trong cuộc thi của
ImageNet, giảm lỗi nhận dạng từ 26% xuống còn 15%
Từ đó trở đi, rất nhiều các viện nghiên cứu, doanh
nghiệp đã sử dụng deep learning như các mô đun core
của các hệ dịch vụ xung quanh
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Problem space: Image classification
Input: eg. 32x32x3 (RGB)
Output: the probability of the image being a
certain class.
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From shallow to deep
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Deep learning
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Spectrum of depth
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Một số mạng neuron sâu và kết quả
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Giới thiệu về mạng neuron tích chập
Xem trong: "F:\Mang Neuron -
2017\refs\intro_cnn.pdf"
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Revolution of depth
Slide trình
bày chi tiết:
"F:\Mang
Neuron -
2017\refs\Dee
pLearnig\Ale
xnet.pdf"
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ZF Net (2013)
Xem trong trang: "F:\Mang Neuron -
2017\refs\DeepLearnig\The 9 Deep Learning Papers
You Need To Know About (Understanding CNNs
Part 3) – Adit Deshpande – CS Undergrad at UCLA
('19).html"
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VGG Net (2014)
Xem trong: "F:\Mang Neuron -
2017\refs\DeepLearnig\ILSVRC_2014.pdf"
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Google lenet
Xem trong : "F:\Mang Neuron -
2017\refs\DeepLearnig\The 9 Deep Learning
Papers You Need To Know About
(Understanding CNNs Part 3) – Adit
Deshpande – CS Undergrad at UCLA
('19).html"
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Microsoft ResNet (2015)
"F:\Mang Neuron -
2017\refs\DeepLearnig\icml2016_tutorial_deep_residual_netw
orks_kaiminghe.pdf"
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2020
So sánh các kiến trúc
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So sánh các kiến trúc
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2323
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Yolo
https://pjreddie.com/darknet/yolo/
"F:\Mang Neuron -
2017\refs\DeepLearnig\YOLO CVPR
2016.pptx“
"F:\Mang Neuron -
2017\refs\DeepLearnig\YOLO_ Real-Time
Object Detection.html"
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Demo
Yolo
Mask-RCNN
Style Transfer
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Tài liệu tham khảo
https://medium.com/@siddharthdas_32104/cnns-
architectures-lenet-alexnet-vgg-googlenet-resnet-and-
more-666091488df5
http://yann.lecun.com/exdb/lenet/
http://cs231n.github.io/convolutional-networks/
http://ufldl.stanford.edu/tutorial/supervised/Convolutional
NeuralNetwork/
http://web.stanford.edu/class/cs231a/lectures/intro_cnn.