Object Detection and Neural Networks

Object Detection and Neural Networks

Assessment

Interactive Video

Computers, Science, Professional Development

10th - 12th Grade

Hard

Created by

Patricia Brown

FREE Resource

This tech talk covers performing object detection using convolutional neural networks (CNNs) in ERDAS IMAGINE. The process is divided into three stages: capturing training data, training the neural network, and applying the trained model to new images. The tutorial demonstrates how to use machine learning layout tools to capture training footprints and image chips, create training samples, and train a CNN. Finally, it shows how to apply the trained model to detect objects in new aerial photos, specifically mapping oil palm locations.

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10 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main topic of the tech talk?

Object detection using convolutional neural networks

Image editing with Photoshop

Data analysis with Excel

Web development with JavaScript

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which tool is used to capture training footprints and chips in the first stage?

MATLAB

AutoCAD

ERDAS IMAGINE

Photoshop

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What type of objects are being detected in the tutorial?

Buildings

Animals

Vehicles

Palm trees

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the spatial model created in the second stage?

To analyze sound waves

To create 3D models

To train a neural network

To edit images

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is produced as a result of training the neural network?

A video file

A machine intellect file

A text document

A spreadsheet

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main task of the second spatial model in the third stage?

To detect and map oil palms

To apply filters to images

To create a new image

To edit video files

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What technology is used to accelerate the processing in the tutorial?

Quantum computing

GPU acceleration

Cloud computing

Blockchain

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