Project - Ship Detection from Satellite Imagery using ML
What you'll learn
- Identify and classify ships in satellite images using machine learning techniques.
- Apply image processing methods to enhance satellite imagery for analysis.
- Implement machine learning models specifically tailored for spatial data recognition.
- Execute a complete project workflow, from data acquisition to model evaluation.
Requirements
- Python Programming Basic Knowledge is Required
Description
Embark on a transformative journey into the world of satellite imagery analysis with our comprehensive Udemy course, "Project - Ships Detection Using Satellite Imagery". Designed for enthusiasts and professionals alike, this course demystifies the process of using cutting-edge machine learning techniques to identify and classify ships in satellite images. Whether you're aiming to bolster your skills in computer vision, eager to dive into spatial data analysis, or looking to apply machine learning in new and exciting ways, this course provides the knowledge and hands-on experience you need.
Final Curriculum Overview:
Module 1 - Introduction and Data Exploration: Start with the basics of the project, exploring the dataset, understanding the applications of machine learning in computer vision, and setting up your development environment.
Module 2 - Run Length Encoding and Decoding: Dive into the specifics of Run Length Encoding (RLE), a critical technique for handling and interpreting satellite image data efficiently. Learn how to work with RLE encodings to create segmented masks for images.
Module 3 - Data Preparation and Preprocessing: Master the art of preparing and preprocessing your data, covering everything from data augmentation to setting up parameters for model building and training.
Module 4 - Image Segmentation using UNET: Delve into image segmentation with a focus on UNET, a powerful convolutional neural network architecture. Understand its components, build your own UNET model, and train it to detect ships in satellite imagery effectively.
Why Choose This Course?
Hands-on Learning: Engage with practical exercises and real-world dataset to solidify your understanding and skills.
Expert Instruction: Learn from an instructor with real-world experience in machine learning and computer vision.
Future-Proof Skills: Gain knowledge that's in demand in industries ranging from maritime navigation to environmental monitoring.
Start your journey towards becoming proficient in satellite imagery analysis with machine learning today. Whether you're enhancing your skillset or pioneering new solutions, this course equips you with the knowledge and tools you need to succeed.
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Who this course is for:
- Whoever interested in Satellite and Aerial image and data science
Instructor
- 4.2 Instructor Rating
- 322 Reviews
- 5,907 Students
- 12 Courses
Spartificial is a platform for students of any domain to learn and work on projects that are solving urgent problems in real world. It is important for a student to learn with an intention for overall technical, social and mental development. We are fan of Project-based multi-domain learning because that's what life is and in our professional life, we are not judged by our test scores or grades but the quality of our work, and our knowledge of real-world.