computer science

Overhead Imagery Research Data Set

Overhead Imagery Research Data Set is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Overhead Imagery Research Data Set rather than just read about it. In short: The Overhead Imagery Research Data Set (OIRDS) is a collection of an open-source, annotated, overhead images that computer vision researchers can use to aid in the development of algorithms. Most computer vision and machine learning algorithms function by training on a large set of example data.

Key takeaways

Overhead Imagery Research Data Set belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Overhead Imagery Research Data Set to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Overhead Imagery Research Data Set from memory before moving on to harder problems.

Reference excerpt

The Overhead Imagery Research Data Set (OIRDS) is a collection of an open-source, annotated, overhead images that computer vision researchers can use to aid in the development of algorithms. Most computer vision and machine learning algorithms function by training on a large set of example data. Further, for many academic and industry researchers, the availability of truth-labeled test data helps drive algorithm research. While a great deal of terrestrial imagery is available on the Internet from various sources, there are few (if any) repositories of overhead imagery. The limited overhead imagery that is found via sources such as Google Earth or Google Maps is copyrighted or may have limited use.

Vehicle Data Set The initial ~1,000 images in the OIRDS is focused on an Automatic Target Detection (ATD) task for passenger vehicles. Passenger vehicles in the OIRDS consist of cars, trucks, vans, & pick-ups. The vehicle data set is composed of USGS and VIVID images. All of these images are color RGB images. The annotations that describe the images are documented in detail in.

Current status OIRDS v1.0 was released in September, 2009. This version contains ~900 annotated images with ~1800 targets identified.

Limitations The current OIRDS data set only has vehicle annotations. It does not include other target types. Additionally, recent trends in computer vision include image context for many detection and classification problems. While researchers are encouraged to provide those annotations, they are not currently provided.

See also Comparison of datasets in machine learning

References

External links Links to Data Sets

https://sourceforge.net/projects/oirds/ – OIRDS Homepage (Includes download) http://www.vision.caltech.edu/Image_Datasets/Caltech101/ Archived 6 December 2013 at the Wayback Machine – Caltech 101 Homepage (Includes download) http://www.vision.caltech.edu/Image_Datasets/Caltech256/ Archived 26 March 2009 at the Wayback Machine – Caltech 256 Homepage (Includes download) http://labelme.csail.mit.edu/ – LabelMe Homepage Links to some sources of OIRDS imagery

United States Geological Survey website – source of a majority of the vehicle data set imagery. DARPA VIVID Program website – source of a small portion of the vehicle data set imagery. Other Links

CVPR 2009 website where OIRDS was demonstrated AIPR-Workshop 2009 website where some OIRDS work was published

Worked examples

Example 1 — a first encounter with Overhead Imagery Research Data Set

Start with the simplest possible case. Write down what Overhead Imagery Research Data Set claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Overhead Imagery Research Data Set before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Overhead Imagery Research Data Set ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Overhead Imagery Research Data Set

In research: Overhead Imagery Research Data Set appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Overhead Imagery Research Data Set in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Overhead Imagery Research Data Set is common in secondary-school and first-year university syllabi. It links to neighbouring topics Datasets in computer vision, so understanding it makes those chapters shorter.
In everyday life: Look for Overhead Imagery Research Data Set outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Overhead Imagery Research Data Set in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Overhead Imagery Research Data Set means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Overhead Imagery Research Data Set out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Overhead Imagery Research Data Set in simple terms?

Why does Overhead Imagery Research Data Set matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Overhead Imagery Research Data Set?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Overhead Imagery Research Data Set.