Chevron Left
Object Localization with TensorFlow に戻る

Coursera Project Network による Object Localization with TensorFlow の受講者のレビューおよびフィードバック



Welcome to this 2 hour long guided project on creating and training an Object Localization model with TensorFlow. In this guided project, we are going to use TensorFlow's Keras API to create a convolutional neural network which will be trained to classify as well as localize emojis in images. Localization, in this context, means the position of the emojis in the images. This means that the network will have one input and two outputs. Think of this task as a simpler version of Object Detection. In Object Detection, we might have multiple objects in the input images, and an object detection model predicts the classes as well as bounding boxes for all of those objects. In Object Localization, we are working with the assumption that there is just one object in any given image, and our CNN model will classify and localize that object. Please note that you will need prior programming experience in Python. You will also need familiarity with TensorFlow. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Convolutional Neural Networks, and optimization algorithms like Gradient Descent but want to understand how to use use TensorFlow to solve computer vision tasks like Object Localization....

Object Localization with TensorFlow: 1 - 10 / 10 レビュー

by Md. F I


Most helpful project. Cleared a lot of things

by Alexandros O


A very good and helpful project for object detection. It would be absolute 5-stars guided-project if there was also an example for multiple object detection.

by Miguel A Q H


It is pretty good for ConvNets beginners, but you need to have prior knowlegde in python(OOP, tf, keras, nn programming)

by Lance O L


If you want to learn the basics and some advanced techniques in TF on object localization, this will help you get to understand each step of the process.

by Md S Q


A fine project for CNN beginers.

by Massimiliano D


very good project

by Balázs N


Thank you!

by Muhammad I


I really liked the course and how it was the next step from a classification problem.

by Kleider S V G


What a good course!

by Oren


Thank you for the organizers and the author. I have learned a thing or two. I did not fully enjoyed. I will avoid giving suggestions as I just cannot put my finger on what bothers me. It just did not work for me. Something was wrong.