This document discusses how deep learning and drones can help find meteorites on Earth more efficiently. Currently, it takes about 100 hours for humans to manually find one meteorite. The document proposes using a drone equipped with cameras and deep learning to automatically scan terrain and detect meteorites. It describes how the team trained several deep learning models on a dataset of meteorite images augmented through techniques like rotation and brightness adjustment. An initial prototype called the Adelie Meteorite Hunter was able to correctly identify meteorites with a low error rate. Ongoing work involves improving the models, drone hardware, and expanding the image dataset to allow fully autonomous meteorite detection missions.

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How Deep Learning and Drones Can
Save the World from Asteroids?
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2. Are asteroids a threat to the Earth?
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4. 4
What’s an Asteroid?
Credit: NASA, JAXA and ESA (montage by Emily
Lakdawalla)

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Impact of Itokawa
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6. Where do they live?

7. 7
What's the solution and why find meteorites?
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Composition affects
threat assessment and
deflection technologies
Why find meteorites?
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9. - It takes 100 man hours to find
one meteorite
- To increase meteorite finds, the
efficiency must be increased
- We have trajectories, but finding
meteorites is difficult
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Current approach to find meteorites
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10. Use a drone combined with Deep learning to
increase fresh meteorite finds
10 @SravanthiSinha

11. 11
Why Deep Learning is the best
solution?
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Traditional Computer Vision - Anomaly Detection
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13. 13
Data-Set
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2 wrong classifications
out of 17000 patches!
Our Deep Learning Solution
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2 correctly labelled meteorites…
124 incorrectly labelled patches…
out of 17000 patches
Our Deep Learning Solution
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Challenges
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17. Unbalanced data!
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Dataset Creation

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How we solved the problem?
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19. rotations
19
reflection resolution brightness saturation
Our meteorite pictures
320
Internet meteorites in field
280
Internet meteorites photoshopped
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635 images... tiny dataset !
32 augmentations per image 21000 images... respectable dataset !
Dataset Augmentation
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~15 million natural images
Leveraging Big Data
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GoogLeNet AlexNet
~6 million parameters ~61 million parameters
Leveraging Pre-trained Networks
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22. 22
Model Ensembling
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Hardware / Software
Each model ~2 hours to train
On a CPU it would be ~1 week !
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24. 24
DEMO
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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter
Functionality in place

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter
Archive images for
future learning.

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

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The ADELIE Meteorite Hunter

39. Image processing
○ Faster inference time
○ Weak classifier
○ Reduce false positives
Improved hardware
○ Autonomous height control (LIDAR)
○ Better camera resolution
○ Longer battery life
○ Additional sensors (IR, hyperspectral?, etc.)
39 @SravanthiSinha
Ongoing work..

40. Amar Shah - Data Scientist,
PhD Student, Cambridge
Robert Citron - Planetary
Scientist, PhD Student, UC
Berkeley
Christopher Watkins, Data
Scientist, PhD Student,
CSIRO, Melbourne
Sravanthi Sinha, Full-Stack
Software Developer, Holberton
School, San Francisco
Peter Jenniskens, Project
Mentor, Meteor Astronomer,
SETI Institute
40
Team
@SravanthiSinha