deep learning for computer vision...computer vision group deep learning for computer vision...
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Computer Vision Group
Deep Learning for Computer Vision
Lecturer: Dr. Laura Leal-TaixeTutors: Caner Hazirbas, Philip Häusser
Vladimir Golkov, John Chiotellis and Lingni Ma
Technische Universität MünchenComputer Vision Group
June 21, 2016
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 1 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
What you will learn in this course
How DL is applied to computer vision problemsPractical experience with the most successful ML methods
Artificial Neural NetworksConvolutional Neural NetworksLong short-term memory (LSTM)
Benefits/drawbacks of the methods when applied to concrete,relevant problemsPractical project experiencesPresentation skills
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 2 / 11
Computer Vision Group
Course Structure
Three-week lecturesOne topic will be discussed each week
ANNCNNLSTM
One exercise will be assigned each week, includingpractical/theoretical questions. Solutions will be discussed inthe following weekOne-month practical project
2-3 people per group, supervised by one tutoraccess to lab computers and discussions with supervisorsduring class hours
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 3 / 11
Computer Vision Group
Course Structure
Three-week lecturesOne topic will be discussed each week
ANNCNNLSTM
One exercise will be assigned each week, includingpractical/theoretical questions. Solutions will be discussed inthe following weekOne-month practical project
2-3 people per group, supervised by one tutoraccess to lab computers and discussions with supervisorsduring class hours
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 3 / 11
Computer Vision Group
Course Structure
Three-week lecturesOne topic will be discussed each week
ANNCNNLSTM
One exercise will be assigned each week, includingpractical/theoretical questions. Solutions will be discussed inthe following weekOne-month practical project
2-3 people per group, supervised by one tutoraccess to lab computers and discussions with supervisorsduring class hours
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 3 / 11
Computer Vision Group
Format of Final Presentation
20min presentation, 5min –10min Q&ARecommended structure
Introduction, problem definitionApproachesExperimental results and discussionsConclusions
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 4 / 11
Computer Vision Group
Evaluation Criteria
Successful fulfillment of all exercisesGained expertise in the topics/projectQuality of the project presentationAttendance of classes/exercises is mandatory! In case ofsickness, medical attest is required.
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 5 / 11
Computer Vision Group
Cool Projects...
FlowNet
convolutional
network
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 6 / 11
Computer Vision Group
Cool Projects...
CAPTCHA Recognition with Active Deep Learning
2015 x 5415 x 54 8 x 27
4 x 1450
500 x 1378 x 1
EA
qy
B4
conv1 pool1 conv pool2
10
%
208 x 27
50
#Iterations
0 1 2 3 4 5 6 7 8
Accura
cy (
%)
0
20
40
60
80
100
added correct and uncertain samples
added random correct samples
added correct and certain samples
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 7 / 11
Computer Vision Group
Cool Projects...
Biomedicine
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 8 / 11
Computer Vision Group
Cool Projects...
Diffusion MRI
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 9 / 11
Computer Vision Group
Study Materials
Pattern recognition and machine learning, by Christopher M.Bishop
Machine learning: a probabilistic perspective, by Kevin P.Murphy
http://www.deeplearningbook.org/ by Ian Goodfellow,Yoshua Bengio and Aaron Courville
Lecturer: Dr. Laura Leal-Taixe Tutors: Caner Hazirbas, Philip Häusser Vladimir Golkov, John Chiotellis and Lingni Ma 10 / 11