Om InfinIT

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1 Om InfinIT

2 InfinIT er Danmarks eneste landsdækkende innovationsnetværk for it. Finansieret af Uddannelses- og Forskningsministeriet. Det er gratis at være medlem. Du får adgang til den nyeste forskning, møder andre virksomheder i den branche og hjælp til at udvikle miniprojekter sammen med danske videninstitutioner

3 MINIPROJEKTER o Søg op til til videninstitutioner (universiteter, GTS er) o Minimum to virksomheder o Ansøgningsfrist 25. oktober o Vil du vide mere, så besøg infinit.dk eller tag fat i mig

4 TEKNOLOGIMORGEN: Deep Learning Henrik Pedersen Head of Visual Computing Lab

5 BUDSKABER Tænk vildt alt er muligt Alle kan lære det Tænk i anvendelser fokusér på det, du er ekspert i

6 NVIDIA GTC, San José, 2018

7 THE DEEP LEARNING REVOLUTION Internet Services Medicine Media & Entertainment Security & Defense Autonomous Machines Image/Video classification Cancer cell detection Video captioning Face recognition Pedestrian detection Speech recognition Diabetic grading Content based search Video surveillance Lane tracking Natural language processing Drug discovery Real time translation Cyber security Recognize traffic signs

8 How AI can help you find the tattoo of your dreams Dennis Mickey Jensen, NVIDIA GTC, San José, 2018

9 KAN ALLE VIRKELIG LÆRE DET?

10 VORES MISSION At gøre Deep Learning teknologien tilgængelig for alle Fokus på billedgenkendelse eller Computer Vision Worksystems Aps

11 Alexandra Instituttet er en almennyttig virksomhed, der hjælper offentlige og private virksomheder med at anvende den nyeste it-forskning og -teknologi.

12 FORMÅLET MED DAGENS ARRANGEMENT Videndeling Hvad er deep learning? Hvad kan man med det? Hvordan kommer man i gang? Behovsafdækning Hvordan hjælper vi jer bedst muligt?

13 WHAT IS DEEP LEARNING?

14 WHAT IS DEEP LEARNING? Neural networks are machine learning algorithms inspired by the structure and function of the brain. They have been around since the 1970s, but the deep learning revolution started just 6-7 years ago mainly due to Big data + GPUs

15 WHY IS DEEP LEARNING SO POWERFUL? Expert written computer program

16 WHY IS DEEP LEARNING SO POWERFUL? Solve complex problems without being an expert you just need data! Database of Cars and Not Cars

17 SO MANY OPPORTUNITIES Colorize gray-scale images Image captioning Turn horses into zebras Turn images into Van Gogh paintings Dream images of fake celebrities Detect human body pose

18 SO MANY OPPORTUNITIES Page 18 CycleGAN

19 CONVOLUTIONAL NEURAL NETWORKS

20 CONVOLUTIONAL NEURAL NETWORKS Encoder Decoder

21 THE ENCODER Encoder Decoder The encoder maps high-dimensional data to a much lower dimension

22 THE DECODER Encoder Decoder

23 DEEP LEARNING IS GEOMETRIC INTELLIGENCE Encoder Decoder Crumpled paper analogy

24 THE NUMBER ONE PROBLEM IN DEEP LEARNING Encoder Decoder Requires labeled training data and lots of it

25 HOW DO YOU GET ENOUGH DATA?

26 ONE POSSIBLE SOLUTION

27 COMPUTER GRAPHICS Generate synthetic images of objects from CAD files Random viewing angle and distance to camera Random lighting conditions Tetris controller Motor

28 APPLICATIONS Image classification

29 APPLICATIONS Image classification Object detection

30 APPLICATIONS Image classification Object detection Pose estimation CAD model Input image Output image

31 AUGMENTED REALITY Weather station

32 TRAINING ROBOTS AND AUTONOMOUS DRONES Page 32 Christian Heider Nielsen

33 IMAGE-TO-IMAGE TRANSFORMATION Fully Convolutional Networks for semantic segmentation Input: Image Output: Image with class labels

34 IMAGE-TO-IMAGE TRANSFORMATION Fully Convolutional Networks for semantic segmentation Input: Image Output: Image with class labels

35 IMAGE-TO-IMAGE TRANSFORMATION Colorizing grayscale images Input: Grayscale image Output: Color image

36 IMAGE-TO-IMAGE TRANSFORMATION Colorizing grayscale images Input: Grayscale image Output: Color image They Shall Not Grow Old - Peter Jackson - WW1

37 IMAGE-TO-IMAGE TRANSFORMATION Image super-resolution Input: Low resolution image Output: High resolution image

38 IMAGE-TO-IMAGE TRANSFORMATION Image completion (inpainting) Input: Low resolution image Output: High resolution image

39 IMAGE-TO-IMAGE TRANSFORMATION Image completion (inpainting) Input: Low resolution image Output: High resolution image

40 OTHER EXAMPLES

41 OTHER EXAMPLES Medical image registration (from hours to seconds) Field segmentation from satellite images Estimation of window dimensions (price)

42 CONTINUOUS SIGN LANGUAGE TRANSLATION Page 42 Søren Rasmussen Kristian Tølbøl Sørensen

43 SATELLITE DATA Bygningsdetektion Input Ground truth Resultat Karsten Østergaard Noe

44 BUDSKABER Alt er muligt tænk vildt! Alle kan lære det Tænk i anvendelser fokusér på det, du er ekspert i

45 BUDSKABER Alt er muligt tænk vildt! Alle kan lære det Tænk i anvendelser fokusér på det, du er ekspert i Myter og barrierer Man skal have masser af data for at komme i gang Man skal investere i dyr hardware for at komme i gang Man skal være deep learning ekspert for at komme i gang

46 BUDSKABER Alt er muligt tænk vildt! Alle kan lære det Tænk i anvendelser fokusér på det, du er ekspert i

47 SÅ HVORDAN KOMMER JEG I GANG? Tag et gratis onlinekursus eller deltag i en af vores workshops Fundamentals of Deep Learning Computer Vision

48 FORMÅLET MED DAGENS ARRANGEMENT Behovsafdækning Hvordan hjælper vi jer bedst muligt? Fremadrettet har vi også brug for virksomheder til Case-forløb Følgegruppe

49 SPØRGSMÅL?