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Ryan Ahmed
In this project, we will train a deep learning model based on Convolutional Neural Networks (CNNs) to detect ships in the satellite images. Satellite imagery are critical in many applications such as defense, agriculture, surveillance and intelligence. This...
Read more
In this project, we will train a deep learning model based on Convolutional Neural Networks (CNNs) to detect ships in the satellite images. Satellite imagery are critical in many applications such as defense, agriculture, surveillance and intelligence. This...
Read more
In this project, we will train a deep learning model based on Convolutional Neural Networks (CNNs) to detect ships in the satellite images. Satellite imagery are critical in many applications such as defense, agriculture, surveillance and intelligence. This project aims at detecting large vessels (ships) in sea from satellite images using Artificial Intelligence. This project is an introductory project for beginners in deep learning and computer vision.
Register for this course and see more details by visiting:
OpenCourser.com/course/slwuve/deep
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Teaches ship detection in satellite images using Convolutional Neural Networks (CNNs), which is standard in the computer vision industry
Suitable for beginners in deep learning and computer vision, providing a strong foundation
Involves hands-on labs and interactive materials, including satellite imagery
Taught by Ryan Ahmed, an instructor with extensive experience in deep learning and computer vision
Save this course
Save Deep Learning 101: Detecting Ships from Satellite Imagery to your list so you can find it easily later:
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Reviews summary
Ship detection course for beginners
This course on deep learning for ship detection is great for beginners in the field. Students appreciate the clear explanations and practical examples.
Introductory course for beginners in deep learning and computer vision.
Explanations are clear and easy to follow.
Course provides practical examples.
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Deep Learning 101: Detecting Ships from Satellite Imagery with these
activities:
Review the basics of Convolutional Neural Networks (CNNs)
Show steps
Completing this activity will refresh your knowledge on CNNs, which are a key concept in this course.
Browse courses on
Convolutional Neural Networks
Show steps
-
Read an article or watch a video tutorial on the basics of CNNs
-
Complete a few practice exercises on CNNs
Follow a tutorial on how to use a deep learning framework for ship detection
Show steps
Completing this activity will help you learn how to use a deep learning framework to detect ships in satellite images.
Browse courses on
Deep Learning Frameworks
Show steps
-
Find a tutorial on how to use a deep learning framework for ship detection
-
Follow the tutorial and complete the exercises
-
Apply what you learned to a project of your own
Attend a workshop or seminar on ship detection in satellite imagery
Show steps
This activity will allow you to learn from experts in the field of ship detection and network with other professionals.
Browse courses on
Satellite Imagery
Show steps
-
Find a workshop or seminar on ship detection in satellite imagery
-
Register for the event
-
Attend the event and participate in the discussions
-
Network with other attendees
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or discussion forum for students taking this course
Show steps
This activity will allow you to learn from and collaborate with other students in the course.
Browse courses on
Satellite Imagery
Show steps
-
Find a study group or discussion forum for students taking this course
-
Join the group or forum
-
Participate in the discussions and ask questions
Practice identifying ships in satellite images
Show steps
This activity will help you develop the skills needed to identify ships in satellite images, which is a key task in this course.
Browse courses on
Satellite Imagery
Show steps
-
Find a dataset of satellite images containing ships
-
Load the dataset into a computer vision library
-
Write a program to identify ships in the images
-
Test your program on unseen satellite images
Volunteer to help with a project that involves ship detection in satellite imagery
Show steps
This activity will allow you to gain practical experience in ship detection and contribute to a real-world project.
Browse courses on
Satellite Imagery
Show steps
-
Find a project that involves ship detection in satellite imagery
-
Contact the project organizers and offer to volunteer
-
Complete the volunteer training
-
Participate in the project activities
Write a blog post or article about the challenges and opportunities of ship detection in satellite imagery
Show steps
This activity will help you develop your understanding of the challenges and opportunities of ship detection in satellite imagery.
Browse courses on
Satellite Imagery
Show steps
-
Research the challenges and opportunities of ship detection in satellite imagery
-
Develop an outline for your blog post or article
-
Write your blog post or article
-
Edit and proofread your writing
-
Publish your blog post or article
Create a presentation on the applications of ship detection in satellite imagery
Show steps
This activity will allow you to apply your knowledge of ship detection to a real-world problem.
Browse courses on
Satellite Imagery
Show steps
-
Research the applications of ship detection in satellite imagery
-
Develop a presentation outline
-
Create a presentation that includes visuals and examples
-
Practice your presentation
-
Deliver your presentation to a group of classmates or colleagues
Review the basics of Convolutional Neural Networks (CNNs)
Show steps
Completing this activity will refresh your knowledge on CNNs, which are a key concept in this course.
Browse courses on
Convolutional Neural Networks
Show steps
Show steps
Show steps
- Read an article or watch a video tutorial on the basics of CNNs
- Complete a few practice exercises on CNNs
Follow a tutorial on how to use a deep learning framework for ship detection
Show steps
Completing this activity will help you learn how to use a deep learning framework to detect ships in satellite images.
Browse courses on
Deep Learning Frameworks
Show steps
Show steps
Show steps
- Find a tutorial on how to use a deep learning framework for ship detection
- Follow the tutorial and complete the exercises
- Apply what you learned to a project of your own
Attend a workshop or seminar on ship detection in satellite imagery
Show steps
This activity will allow you to learn from experts in the field of ship detection and network with other professionals.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Find a workshop or seminar on ship detection in satellite imagery
- Register for the event
- Attend the event and participate in the discussions
- Network with other attendees
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or discussion forum for students taking this course
Show steps
This activity will allow you to learn from and collaborate with other students in the course.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Find a study group or discussion forum for students taking this course
- Join the group or forum
- Participate in the discussions and ask questions
Practice identifying ships in satellite images
Show steps
This activity will help you develop the skills needed to identify ships in satellite images, which is a key task in this course.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Find a dataset of satellite images containing ships
- Load the dataset into a computer vision library
- Write a program to identify ships in the images
- Test your program on unseen satellite images
Volunteer to help with a project that involves ship detection in satellite imagery
Show steps
This activity will allow you to gain practical experience in ship detection and contribute to a real-world project.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Find a project that involves ship detection in satellite imagery
- Contact the project organizers and offer to volunteer
- Complete the volunteer training
- Participate in the project activities
Write a blog post or article about the challenges and opportunities of ship detection in satellite imagery
Show steps
This activity will help you develop your understanding of the challenges and opportunities of ship detection in satellite imagery.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Research the challenges and opportunities of ship detection in satellite imagery
- Develop an outline for your blog post or article
- Write your blog post or article
- Edit and proofread your writing
- Publish your blog post or article
Create a presentation on the applications of ship detection in satellite imagery
Show steps
This activity will allow you to apply your knowledge of ship detection to a real-world problem.
Browse courses on
Satellite Imagery
Show steps
Show steps
Show steps
- Research the applications of ship detection in satellite imagery
- Develop a presentation outline
- Create a presentation that includes visuals and examples
- Practice your presentation
- Deliver your presentation to a group of classmates or colleagues
Career center
Learners who complete Deep Learning 101: Detecting Ships from Satellite Imagery will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers develop and implement systems that allow computers to interpret and understand images. This course helps build a foundation in deep learning, a core technology in Computer Vision, and covers Convolutional Neural Networks, a specific type of neural network commonly used in image-based tasks.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course helps build a foundation in deep learning, a fundamental aspect of Machine Learning, and covers Convolutional Neural Networks, a specialized type of neural network used for image recognition and object detection.
Data Scientist
Data Scientist
Data Scientists use various techniques to gather, store, and analyze data, including machine learning and AI algorithms. This course helps build a foundation in deep learning, an essential tool for Data Scientists, and covers Convolutional Neural Networks, commonly used in image processing tasks, like detecting objects in images.
Image Processing Engineer
Image Processing Engineer
Image Processing Engineers develop and use techniques to enhance, analyze, and interpret images. This course helps build a foundation in deep learning, a powerful tool for image processing, and covers Convolutional Neural Networks, a type of neural network specifically designed for image-based tasks.
Data Analyst
Data Analyst
Data Analysts collect, process, and analyze data to extract meaningful insights. This course helps build a foundation in deep learning, a powerful tool for data analysis, and covers Convolutional Neural Networks, a type of neural network commonly used for image recognition and object detection.
Geospatial Analyst
Geospatial Analyst
Geospatial Analysts use geographic information systems (GIS) to analyze and visualize data. This course helps build a foundation in deep learning, an emerging technology for Geospatial Analysts, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection, essential skills for analyzing satellite imagery.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and implement AI systems. This course helps build a foundation in deep learning, a core technology for AI, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain computer applications. This course helps build a foundation in deep learning, an increasingly important field for Software Engineers to understand, and covers Convolutional Neural Networks, a specialized type of neural network used in image recognition and object detection.
Robotics Engineer
Robotics Engineer
Robotics Engineers design, build, and program robots. This course helps build a foundation in deep learning, an emerging field for Robotics Engineers, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection, critical skills for robot navigation.
Analyst Programmer
Analyst Programmer
Analyst Programmers use programming skills to analyze and solve business problems. This course helps build a foundation in deep learning, a valuable asset for Analyst Programmers, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection, helpful for analyzing images.
Research Scientist
Research Scientist
Research Scientists conduct research in various scientific fields. This course helps build a foundation in deep learning, an important tool for scientific research, and covers Convolutional Neural Networks, a type of neural network used for image processing and object detection.
Computer Scientist
Computer Scientist
Computer Scientists advance the understanding and application of computing technologies. This course helps build a foundation in deep learning, an increasingly important area of computer science, and covers Convolutional Neural Networks, a specialized type of neural network for image processing and object detection.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts ensure the quality of software and other products. This course may be useful in building a foundation in deep learning, an emerging field relevant to software testing, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course may be useful in building a foundation in deep learning, an emerging technology for data management, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection.
IT Project Manager
IT Project Manager
IT Project Managers plan and execute IT projects. This course may be useful in building a foundation in deep learning, an emerging technology in IT, and covers Convolutional Neural Networks, a type of neural network used for image recognition and object detection.
For more career information including salaries, visit:
OpenCourser.com/course/slwuve/deep
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Deep Learning 101: Detecting Ships from Satellite Imagery.
Provides a practical introduction to deep learning using the Python programming language. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for beginners and experienced practitioners alike.
Save
Provides a comprehensive overview of deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for students and researchers in the field.
Provides a comprehensive overview of deep learning for computer vision, covering topics such as image classification, object detection, and segmentation. It valuable resource for both beginners and experienced practitioners in the field.
Save
Provides a comprehensive overview of machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for students and researchers in the field.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as statistical pattern recognition, neural networks, and support vector machines. It valuable resource for students and researchers in the field.
Save
This classic textbook provides a comprehensive foundation in computer vision, covering topics such as image formation, camera calibration, feature extraction, and object recognition. It valuable resource for students and researchers in the field.
Provides a comprehensive overview of computer vision, covering topics such as image formation, camera calibration, feature extraction, and object recognition. It valuable resource for students and researchers in the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/slwuve/deep
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Time
1 hours
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Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Good to know
Teaches ship detection in satellite images using Convolutional Neural Networks (CNNs), which is standard in the computer vision industry
Suitable for beginners in deep learning and computer vision, providing a strong foundation
Involves hands-on labs and interactive materials, including satellite imagery
Taught by Ryan Ahmed, an instructor with extensive experience in deep learning and computer vision
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