The document discusses using AI and deep learning for on-board satellite image analysis. It describes how a company's software called MLOS (Machine Learning Open Studio) can be used to automate the entire AI pipeline for tasks like ship detection from satellite images. MLOS allows users to design, evaluate, and share machine learning algorithms using a graphical workflow interface. It provides access to different hardware resources and can scale experiments on demand.

1. AI and Deep Learning for On-Board
Satellite Image Analysis
Caroline Pacheco

2. Denis Caromel,
CEO
François Tournesac,
CSO
Fabien Viale,
CTO
Company
• Founded in 2007 by Denis Caromel in Sophia-Antipolis, Spin-off of INRIA
• Addressing $80 Billion Hybrid Cloud Market with 27% CAGR
• Disruptive Patented Technology w/ Exceptional Business Outcomes
• 60% of the revenue from international
Workload automation
Machine learning open studio

3. AE Architectural Vision
Workflow Studio: Graphical interface for creating your workflows.
Automation Dashboard: Runs and manages jobs and service. It includes Job
planner allows to set up custom and recurrent execution of selected workflows
based on calendar rules.
Scheduling: Submits workflows, monitor their execution and retrieve result.
Resource Manager: Aggregates and manage resources from different infrastructures,
such as private or public clouds resources (OpenStack, CloudStack, VMWare, Windows
Azure, Amazon EC2, Numergy, etc.).

4. All in one solution
includes 3 addons:
Job Planner (JP),
Cloud Watch (CW),
Cloud Automation (CA).

5. Artificial Intelligence (AI)
AI Systems are based on
mathematical functions that
exhibit intelligence in a given
domain.
Machine Learning gives to
computers the capability to
learn without being explicitly
programmed.
Support Vector Machines Linear Regression K-means
Naives Bayes K-Nearest Neighbors (KNN)
It's not easy due to its feature extraction step!
Some traditional Machine Learning techniques

6. Artificial Intelligence (AI)
How to deploy efficiently and scalable AI
solutions to solve real-world applications?
Neural networks
Deep learning automates the
feature extraction step and it presents a high accuracy
for different applications.

7. AI Challenges
AE solution can deal with these challenges!
Visdom

8. MLOS
Machine Learning Open Studio
ML pipeline automation

9. https://www.youtube.com/watch?v=mbrQxCf4lqM
MLOS Overview

10. Automate the whole AI pipeline
on any infrastructure
MLOS Value Proposition
Data
preparation
Model
training
Model
optimization
Model
evaluation
Deployment Prod
Simple
Portable
Scalable
Pre-built data connectors
Pre-built generic data prep. tasks
Pre-built containers
Pre-built pipeline templates
More …
Any infrastructure
Any resource: CPU, GPU, FPGA,
…
Graphical workflow representation
Governance on workflow execution
Error management and alerting
Python SDK
Jupyter integration

11. AI Pipeline Introduction
Data
preparation
Model
training
Model
optimization
Model
evaluation
Deployment
Data manipulation
Data blending
Missing values
handling
Feature generation
Dimensionality
reduction
Outlier removal
Normalization
Partitioning
…
Model training
Bag of models
Model selection
Ensemble models
Own ensemble
models
External models
Import existing
models
Model factory
Clustring
…
No iterations
Number of neuronal
layers
Size of neuronal
layer
…
Performance
measures
Accuracy
Cross validation
ROC curve
…
File & DBs
Dashboards
Rest APIs
SQL Code Export
Reporting
…
Prod

12. Image Analysis On-board Satellites

13. FEATURES
● Introduce Artificial Intelligence technologies in the
aerial/satellite image chain
● Give them autonomy, opening up many
opportunities for remote sensing with a capacity
for reaction
● Creation of large database of labeled aerial
images dedicated to learning
● Evaluate performances on concrete settings (use
cases, data, hardware)
BENEFITS
● A collaborative platform to design, evaluate and
share ML algorithms
● Direct access to diverse hardware (different GPU,
FPGA, Clouds, On-premise)
● On-demand scalability for diverse experiments
DL for On-Board Satellite Image Analysis

14. FEATURES
● Find ships directly on satellite images as
quickly as possible by semantic segmentation
using Deep Learning
● Semantic segmentation on binary images of
ships: objects from the same class with large
variability in terms of scale, pose, viewpoint
and background
BENEFITS
● Automatic detection of ships to support the
maritime industry to increase knowledge,
anticipate threats, trigger alerts, and improve
efficiency at sea
ProActive workflow for ship detection on satellite images
Input image
Output image
Non-public dataset: https://www.kaggle.com/c/airbus-ship-detection
Ship Detection on Satellite Images

15. Ship Detection on Satellite Images
https://drive.google.com/file/d/1-cMAXl-14cYJYirPlZGjPbULgZMo4rCK/view?usp=sharing
Video Demonstration

16. Video: https://www.youtube.com/watch?time_continue=27&v=73wRUJ-GITI
Auto ML: An Open Solution

17. Job Analytics – Overview

18. Monitoring Progress of your Jobs

19. Video: https://www.youtube.com/watch?v=yqBB702YO70
Analyzing Results

20. Colocar o script da tela
Thank you!
MLOS: https://try.activeeon.com/