Price: $48.00
(as of Dec 28,2024 02:43:02 UTC – Details)
Publisher : LAP LAMBERT Academic Publishing (July 20, 2023)
Language : English
Paperback : 52 pages
ISBN-10 : 6206751015
ISBN-13 : 978-6206751014
Item Weight : 3.39 ounces
Dimensions : 5.91 x 0.12 x 8.66 inches
Object Detection and Classification on Satellite Imagery: Using Computer Vision and A.I.
Satellite imagery has become an invaluable tool for a wide range of applications, from urban planning to disaster response. One of the key challenges in analyzing satellite imagery is the detection and classification of objects within the images. This task can be time-consuming and labor-intensive when done manually, which is where computer vision and artificial intelligence (A.I.) come into play.
Computer vision algorithms can be trained to automatically detect and classify objects within satellite imagery, such as buildings, roads, and vegetation. By leveraging A.I. technologies, these algorithms can learn to recognize patterns and features within the images, allowing for more efficient and accurate object detection and classification.
One common approach to object detection and classification on satellite imagery is through the use of convolutional neural networks (CNNs). CNNs are a type of deep learning algorithm that is well-suited for analyzing visual data, making them ideal for tasks like object detection in images. By training a CNN on a large dataset of labeled satellite imagery, the algorithm can learn to identify and classify objects with high accuracy.
In addition to CNNs, other computer vision techniques such as image segmentation and feature extraction can also be used to enhance object detection and classification on satellite imagery. These techniques can help to further refine the detection and classification process, leading to more precise results.
Overall, the combination of computer vision and A.I. technologies holds great potential for improving object detection and classification on satellite imagery. By automating this process, researchers and analysts can save time and resources, while also gaining valuable insights from the vast amount of data that satellite imagery provides.
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