Image Analysis Using Ia And Deep Learning In Arcgis Pro

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Image Analysis Using Ia And Deep Learning In Arcgis Pro
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.28 GB | Duration: 1h 10m

Unlocking the Power of Artificial Intelligence for Geospatial Insights and Automation.

[b]What you'll learn[/b]

Basic Concepts of AI and Deep Learning.

Application of AI and Deep Learning in ArcGIS Pro.

Workflow for creating models with Deep Learning and ArcGIS Pro.

ESRI Pretrained Models.

Creating your own model from high-resolution images.

Using Deep Learning tools in ArcGIS Pro.

[b]Requirements[/b]

Have ArcGIS Pro installed.

Basic knowledge of Geographic Information Systems.

[b]Description[/b]

Welcome to the course Image Analysis Using IA and Deep Learning in ArcGIS Pro!In this course, you will dive into the exciting world of artificial intelligence (AI) and deep learning, applied to geographic information systems (GIS). Throughout this journey, we will explore how AI is transforming geospatial analysis, providing us with powerful tools to solve complex problems across various industries, from car detection and crowd counting to vegetation analysis and urban planning.The course is divided into two parts:Theoretical Part: We will lay the foundation to understand the fundamental concepts of AI, Machine Learning, and Deep Learning. Additionally, we will see how these integrate with GIS systems and explore some of the most impactful applications of Deep Learning in this field. We will also examine the workflow needed to develop your own models and review the pre-trained models offered by ESRI, giving you a clear idea of their utility in spatial analysis.Practical Part: We will move from theory to action with a series of hands-on exercises. We will begin with five examples of pre-trained models that will allow you to familiarize yourself with the power of these tools for tasks like car detection, crowd counting, construction footprint digitization, and plant disease identification. Finally, we will wrap up with an exciting project where you will create your own Deep Learning model to identify frailejón plants in a high-resolution orthophoto, using the advanced tools of ArcGIS Pro.This course is designed for both beginners and those with prior experience to make the most of it. You will not only learn technical concepts but also gain practical skills that you can apply to your geospatial analysis projects.Thank you for joining this adventure! I am confident that by the end, you will feel more empowered to tackle the challenges of spatial analysis with AI and Deep Learning. Let's get started!

Overview

Section 1: Course Introduction

Lecture 1 Welcome to the course

Section 2: Introduction

Lecture 2 Introduction to AI and Deep Learning

Lecture 3 Geographic Information Systems and Deep Learning

Lecture 4 Applications of Deep Learning in Geographic Information Systems

Lecture 5 Workflow for Training a Deep Learning Model in ArcGIS Pro

Lecture 6 Introduction to ESRI's Pre-Trained Models in ArcGIS Pro

Lecture 7 Hardware Requirements

Lecture 8 Install Deep Learning Libraries

Lecture 9 Image Analysis Tools

Section 3: Working with ESRI Pre-trained Models in ArcGIS Pro

Lecture 10 ESRI Pre-trained Models in ArcGIS Living Atlas

Lecture 11 Download the Material for the Practical Exercises

Lecture 12 Exercise 1 - Car Detection

Lecture 13 Exercise 2 - Crowd Counting

Lecture 14 Exercise 3 - Building Footprint (Digitization)

Lecture 15 Exercise 4 - Plant Disease Detection.

Lecture 16 Exercise 5 - Tree Detection

Section 4: Create a Model for Frailejón Detection Using Deep Learning Tools

Lecture 17 Introduction to Frailejones

Lecture 18 Prepare Training Data

Lecture 19 Train Model

Lecture 20 Run Model - Part 1

Lecture 21 Run Model - Part 2

Lecture 22 Final Message

Specialists in Geographic Information Systems.,Environmental engineers.Geographers.,Researchers and academics.,Photogrammetrists and cartographers.,Urban planners and designers.,Civil engineers and surveyors.,Agronomists.,Engineers in general.

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