Udemy - Deep Learning Application for Earth Observation

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[ DevCourseWeb.com ] Udemy - Deep Learning Application for Earth Observation
  • Get Bonus Downloads Here.url (0.2 KB)
    • ~Get Your Files Here ! 1. Introduction
    • 1. Introduction.mp4 (39.0 MB)
    • 2. Convolution neural network.mp4 (39.3 MB)
    • 3. Resources to learn deep learning.html (0.9 KB)
    • 4. Notebooks and codes.html (0.4 KB)
    2. Deep learning environment setup
    • 1. Overview of this section.mp4 (4.4 MB)
    • 2. Local environment vs Google Colab.mp4 (14.7 MB)
    • 3. Tensorflow installation.mp4 (88.6 MB)
    • 4. Tensorflow in jupyter notebook.mp4 (14.4 MB)
    • 5. Installation of matplotlib, gdal and rasterio.mp4 (22.7 MB)
    • 6. Tensorflow in google colab.mp4 (45.9 MB)
    • 7. Deep learning basic questions.html (0.2 KB)
    3. Deep learning dataset preparation using ArcGIS Pro
    • 1. Required dataset for this lecture.html (0.9 KB)
    • 2. Create area of interest in ArcGIS pro.mp4 (110.1 MB)
    • 3. Download sentinel2 MSI imagery from GEE.mp4 (105.6 MB)
    • 4. Create the output imagery (mask imagery).mp4 (99.3 MB)
    • 5. Create image and mask tiles using arcgis pro.mp4 (195.5 MB)
    • 6. Deep learning dataset preparation quiz.html (0.2 KB)
    4. Open source solution for data preparation (geotile)
    • 1. Overview of this section.html (0.7 KB)
    • 2. About the input dataset.mp4 (36.1 MB)
    • 3. Introduction to geotile package.mp4 (13.9 MB)
    • 4. Image and Mask tiles using GeoTile.mp4 (152.6 MB)
    • 5. DL training dataset preparation using open-source solution.html (0.2 KB)
    5. Image classification
    • 1. Overview of this lecture.html (1.2 KB)
    • 2. Introduction to image classification.mp4 (51.6 MB)
    • 3. About dataset.mp4 (45.2 MB)
    • 4. Image classification deep learning model.mp4 (195.0 MB)
    6. Deep learning object detection
    • 1. Overview of this section.html (0.3 KB)
    • 2. Object detection introduction.mp4 (21.1 MB)
    • 3. About dataset.mp4 (34.0 MB)
    • 4. Object detection using YOLOv4.mp4 (199.6 MB)
    7. Image segmentation (Binary class)
    • 1. Overview of this section.html (0.4 KB)
    • 2. About dataset.mp4 (29.0 MB)
    • 3. Building detection.mp4 (138.3 MB)
    8. Image segmentation (Multi-class)
    • 1. Overview of this section.html (0.5 KB)
    • 2. Land use Land cover mapping.mp4 (100.7 MB)
    • 3. Convert image to numpy file.mp4 (14.0 MB)
    • 4. Convert numpy file to image.mp4 (31.2 MB)
    9. Landslide detection
    • 1. Overview of this section.html (0.5 KB)
    • 2. Landslide inventory detection using CNN.mp4 (276.7 MB)
    • 3. Attention U-Net introduction.mp4 (30.7 MB)
    • 4. Landslide detection using SAR dataset.mp4 (274.7 MB)
    • 5. Bonus lecture.html (2.2 KB)
    • Bonus Resources.txt (0.4 KB)

Description

Deep Learning Application for Earth Observation



https://DevCourseWeb.com

Published 10/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 39 lectures (4h 49m) | Size: 2.42 GB

Satellite Image processing using Deep Learning Neural Network

What you'll learn
Practical example use case of deep learning for satellite imagery
Satellite imagery analysis
Object detection
Image classification
Image segmentation
Keras, Tensorflow
ArcGIS Pro (Optional)
QGIS (Optional)

Description
Deep Learning is a subset of Machine Learning that uses mathematical functions to map the input to the output. These functions can extract non-redundant information or patterns from the data, which enables them to form a relationship between the input and the output. This is known as learning, and the process of learning is called training.



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Udemy - Deep Learning Application for Earth Observation

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2.4 GB
seeders:1
leechers:21
Udemy - Deep Learning Application for Earth Observation

Torrent hash: CF22212D214D221E38CEE7E339E90DBEB429BDAF