Introduction. Briefing image classification, object detection, and deep learning.

1. 1
深度學習及影像辨識
(Deep Learning and Image Recognition)
fangkuoyu@gmail.com
12/26/2017

2. 圖像分類及圖像檢測
2
classification
detection
Source: https://github.com/kjw0612/awesome-deep-vision

3. 圖像分類及圖像檢測
3
Source: Hardware Architectures for Deep Neural Network (MIT) and
Convolutional Neural Networks for Visual Recognition (Stanford)

4. 機器學習/深度學習/軟體⽀支援
(machine learning/deep learning/software support)
圖像分類及圖像檢測
(classification and detection — case study)
其他圖像應⽤用
(other interesting applications)
內容⼤大綱
4
3
2
1

5. Machine Learning Landscape
5Source: http://www.techjini.com/blog/machine-learning/

6. Supervised Learning
6
Source: http://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/tutorial/
plot_ML_flow_chart.html

7. Supervised Learning
7
Binary
Classification
Source: Real-World Machine Learning

8. Unsupervised Learning
8
Source: http://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/tutorial/
plot_ML_flow_chart.html

9. Unsupervised Learning
9Source: http://adilmoujahid.com/posts/2016/06/introduction-deep-learning-python-caffe/
Cluster Analysis

10. Supervised v.s. Unsupervised
10
Problem Formulation ?!

11. Traditional v.s. Deep Learning
11
Source: http://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/tutorial/
plot_ML_flow_chart.html

12. Convolutional Neural Network
12
Source: https://adeshpande3.github.io/adeshpande3.github.io/A-Beginner%27s-Guide-To-
Understanding-Convolutional-Neural-Networks/

13. Convolutional Neural Network
13
convolution
with
3x3 filter
max polling
with
2x2 pool
Source: https://cambridgespark.com/content/tutorials/convolutional-
neural-networks-with-keras/index.html

14. Data-Driven Approach
14
Source: http://ogrisel.github.io/scikit-learn.org/sklearn-tutorial/auto_examples/tutorial/
plot_ML_flow_chart.html

15. Image Dataset
15
Source: https://cambridgespark.com/content/tutorials/convolutional-
neural-networks-with-keras/index.html
MNIST CIFAR-10 / CIFAR-100

16. ImageNet Dataset
16Source: http://www.image-net.org
14,197,122 images
21,841 synsets

17. Deep Learning Software
17Source: https://www.svds.com/getting-started-deep-learning/

18. Deep Learning Software
18Source: https://mobile.twitter.com/fchollet/status/871089784898310144

19. 機器學習/深度學習/軟體⽀支援
(machine learning/deep learning/software support)
圖像分類及圖像檢測
(classification and detection — case study)
其他圖像應⽤用
(other interesting applications)
內容⼤大綱
19
3
2
1