alexey gruzdev a.s.gruzdev@yandex€¦ · alexey gruzdev a.s.gruzdev@yandex.ru january 27, 2017...

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Overview of what was investigated

Alexey Gruzdeva.s.gruzdev@yandex.ru

January 27, 2017

Alexey Gruzdev Overview of what was investigated

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Agenda

1 Previous activitiesObject DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

2 Current activitiesReinforcement LearningDeep Reinforcement Learning

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Object Detection problem formulation

Input: RGB or grayscale image

Task:

find all existing objects on the image

for each object, calculate ”accurate” bounding box

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Datasets for Object Detection

PASCAL Visual Object Classes Challenge 2012

SUN: Large-scale Scene Recognition from Abbey to Zoo

ImageNet Large Scale Visual Recognition Challenge

Microsoft Common Objects in Context

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Semantic Segmentation problem formulation

Input: RGB or grayscale image

Task:

label each pixel to particular class

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Style Transfer

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Input data - set of training/testing images. For each trainingimage also known its class (the degree of severity)

Output data - A clinician has rated the presence of diabeticretinopathy in each image on a scale of 0 to 4, according to thefollowing scale:

0 - No DR

1 - Mild

2 - Moderate

3 - Severe

4 - Proliferative DR

Goal: - create algorithm, which is able to determine the degree ofseverety for input retina image.

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Object DetectionSemantic SegmentationStyle TransferDiabetic Retinopathy Detection

Diabetic Retinopathy Detection

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Reinforcement LearningDeep Reinforcement Learning

Reinforcement Learning

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Reinforcement LearningDeep Reinforcement Learning

Deep Reinforcement Learning

Motivation:

Deep means that at least one function is approximated byDeep Neural Network

Reinforcement Learning is useful for robotics, continuouscontrol, decision making

Data is available. Thanks to OpenAI!

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Reinforcement LearningDeep Reinforcement Learning

Questions?

Alexey Gruzdev Overview of what was investigated

Previous activitiesCurrent activities

Reinforcement LearningDeep Reinforcement Learning

Alexey Gruzdev Overview of what was investigated