Deep Learning in Computer Vision (Coursera)

Deep Learning in Computer Vision (Coursera)

Añade tu reseña
Añadir a Mis FavoritosAñadido a tus favoritosEliminado de tus favoritos 0
Añadir para comparar

Descripción de “Deep Learning in Computer Vision (Coursera)”

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models.

We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI.

Course 6 of 7 in the Advanced Machine Learning Specialization

Syllabus

WEEK 1 – 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!

WEEK 2 – 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.

WEEK 3 – 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.

WEEK 4 – 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.

WEEK 5 – Image segmentation and synthesis

In the last module of this course, we shall consider problems where the goal is to predict entire image. These are semantic image segmentation and image synthesis problems. Modern CNNs tailored for segmentation employ multiple specialised layers to allow for efficient training and inference. Lastly, we will get to know Generative Adversarial Networks — a bright new idea in machine learning, allowing to generate arbitrary realistic images.

Especificaciones: Deep Learning in Computer Vision (Coursera)

Curso ofrecido por
Disponibilidad

✔ Disponible

Plataforma

Universidad

Impartido por

Alexey Artemov Anton Konushin

País

Russia

Nivel, duración y fechas
Nivel

Avanzado

Fecha

04/05/2020

Duración

5 semanas

Tiempo necesario

4-5 horas/semana

Idioma del curso
Idioma vehicular

Inglés

Subtítulos

Inglés-Coreano

Exámenes y Certificados
Certificados

Certificado de Pago

Exámenes/Proyectos

Con Examen/Proyecto Final de pago

User Reviews

0.0 fuera de 5
0
0
0
0
0
Write a review

Aún no hay reseñas.

Se el primero en opinar sobre “Deep Learning in Computer Vision (Coursera)”

Tu dirección de correo electrónico no será publicada. Los campos obligatorios están marcados con *

Antes de enviar tu opinión, has de aceptar nuestra política de cookies y privacidad

Deep Learning in Computer Vision (Coursera)
Deep Learning in Computer Vision (Coursera)

Este sitio web utiliza cookies para un correcto funcionamiento. Si continúas navegando estás dando tu consentimiento para estas cookies y aceptas nuestra política de cookies, clic para más información.

ACEPTAR
Aviso de cookies
Comparar artículos
  • Total (0)
Comparar
0