walk through intuitively on how Neural Network ( here i use a CNN model ) see the world

1. 1. INTUITION – HOW AI LEARN
2. PUT IT IN CONTEXT – PNEUMONIA
3. PLAN OF ATTACK– HOW TO DO IT
4. DEMO – JUPYTER NOTEBOOK
5. GENERALIZATION

2. Is this an apple ?
apple apple not apple
apple apple not appleapple apple not apple
...

3. apple apple
...
not appleapple apple not apple
Neural Network
Training
Validataion
Labels
Features
apple apple not apple
1/3 2/3Performance :
(accuracy)
2/3 =67%
Prediction apple apple apple

4. INPUTs :
(image + label)
Feed to
NN
NN
predicts
labels
BUILD A MODEL TO CLASSIFY PNEUMONIA
The Neural Networks
Model Prediction
. .
Pneumonia Normal
Normal
Pneumonia
...

5. All done in one Jupyter notebook
1.Get
data
2.Data
Process
&
Explore
3.1
framework
(TF, Keras,
Torch...etc)
3.2 loss &
optimize
function
3.Neural Network architecture
Deep learning
4.Prediction
3.3 train &
validate

6. DEMO
Demo

8. THE SAME CONCEPT CAN BE
APPLIED TO OTHER
SCENARIOS

9. INPUTs :
Images of objects of interests
Feed
to NN
Object
shapes
BUILD A MODEL TO LEARN VIDEO SEMANTIC SEGMENTATION
(ENET)
Model Prediction:
The Neural Networks

10. INPUTs :
Images of objects of interests
Feed
to NN
Object
labels +
location
BUILD A MODEL TO LEARN OBJECT DETECTION IN VIDEO
(SSD)
Model Prediction:
The Neural Networks

11. Raw input abdominal CT
scan
Output segment
BUILD A MODEL TO SEGMENT 4D CT SCAN ORGANS
(NIFTYNET)

12. BUILD A MODEL TO LEARN TO PLAY ANGRY BIRD

13. PARKING

14. Predictedoriginal