Acerca de este Curso
4.0
70 calificaciones
13 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 27 horas para completar

Sugerido: 5 weeks of study...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 27 horas para completar

Sugerido: 5 weeks of study...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
3 horas para completar

Introduction to image processing and computer vision

Welcome to the "Deep Learning for Computer Vision“ course! In the first introductory week, you'll learn about the purpose of computer vision, digital images, and operations that can be applied to them, like brightness and contrast correction, convolution and linear filtering. These simple image processing methods solve as building blocks for all the deep learning employed in the field of computer vision. Let’s get started!...
Reading
8 videos (Total 54 min), 2 quizzes
Video8 videos
Digital images3m
Structure of human eye and vision6m
Color models15m
Image processing goals and tasks2m
Contrast and brightness correction5m
Image convolution7m
Edge detection8m
Quiz1 ejercicio de práctica
Basic image processing10m
Semana
2
Horas para completar
4 horas para completar

Convolutional features for visual recognition

Module two revolves around general principles underlying modern computer vision architectures based on deep convolutional neural networks. We’ll build and analyse convolutional architectures tailored for a number of conventional problems in vision: image categorisation, fine-grained recognition, content-based retrieval, and various aspect of face recognition. On the practical side, you’ll learn how to build your own key-points detector using a deep regression CNN. ...
Reading
12 videos (Total 91 min), 2 quizzes
Video12 videos
AlexNet, VGG and Inception architectures11m
ResNet and beyond10m
Fine-grained image recognition5m
Detection and classification of facial attributes6m
Content-based image retrieval7m
Computing semantic image embeddings using convolutional neural networks8m
Employing indexing structures for efficient retrieval of semantic neighbors9m
Face verification6m
The re-identification problem in computer vision5m
Facial keypoints regression6m
CNN for keypoints regression5m
Quiz1 ejercicio de práctica
Convolutional features for visual recognition24m
Semana
3
Horas para completar
3 horas para completar

Object detection

In this week, we focus on the object detection task — one of the central problems in vision. We start with recalling the conventional sliding window + classifier approach culminating in Viola-Jones detector. Tracing the development of deep convolutional detectors up until recent days, we consider R-CNN and single shot detector models. Practice includes training a face detection model using a deep convolutional neural network....
Reading
13 videos (Total 46 min), 2 quizzes
Video13 videos
Sliding windows3m
HOG-based detector2m
Detector training3m
Viola-Jones face detector5m
Attentional cascades and neural networks3m
Region-based convolutional neural network3m
From R-CNN to Fast R-CNN5m
Faster R-CNN4m
Region-based fully-convolutional network2m
Single shot detectors3m
Speed vs. accuracy tradeoff1m
Fun with pedestrian detectors1m
Quiz1 ejercicio de práctica
Object Detection16m
Semana
4
Horas para completar
4 horas para completar

Object tracking and action recognition

The fourth module of our course focuses on video analysis and includes material on optical flow estimation, visual object tracking, and action recognition. Motion is a central topic in video analysis, opening many possibilities for end-to-end learning of action patterns and object signatures. You will learn to design computer vision architectures for video analysis including visual trackers and action recognition models....
Reading
11 videos (Total 74 min), 2 quizzes
Video11 videos
Optical flow5m
Deep learning in optical flow estimation5m
Visual object tracking5m
Examples of visual object tracking methods13m
Multiple object tracking5m
Examples of multiple object tracking methods8m
Introduction to action recognition6m
Action classification7m
Action classification with convolutional neural networks5m
Action localization6m
Quiz1 ejercicio de práctica
Video Analysis16m
4.0
13 revisionesChevron Right

Principales revisiones

por SJJun 12th 2018

Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.

Instructores

Avatar

Anton Konushin

Senior Lecturer
HSE Faculty of Computer Science
Avatar

Alexey Artemov

Senior Lecturer
HSE Faculty of Computer Science

Acerca de National Research University Higher School of Economics

National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communications, IT, mathematics, engineering, and more. Learn more on www.hse.ru...

Acerca del programa especializado Advanced Machine Learning

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings....
Advanced Machine Learning

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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