Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.

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Computer Vision con AWS
Woody Borraccino, AI Specialist Solutions Architect, Computer Vision

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The reach of ML is growing
By 2021, global spending on AI
and cognitive technologies will
exceed $50 billion
—IDC
INCREASED SPENDING
By the end of 2024, 75% of
enterprises will shift from
piloting to operationalizing AI
—Gartner
FROM PILOTING TO
OPERATIONALIZING
AI TRANSFORMATION
57% said that AI would
transform their organization in
the next three years
—Deloitte

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Classification Object Detection Segmentation Pose Estimation
Computer Vision challenges
Images from https://gluon-cv.mxnet.io/contents.html

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Model Zoo for Classification
pre-trained models evaluations
graph
https://gluon-cv.mxnet.io/model_zoo/classification.html

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Our mission at AWS
Put machine learning in the
hands of every developer

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VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD DEVELOPMENT
CONTACT
CENTERS
Ground
Truth
AWS Marketplace
for ML
Neo
Augmented
AI
Built-in
algorithms
Notebooks Experiments Processing
Model training
and tuning
Debugger Autopilot
Model
hosting
Model
Monitor
Deep Learning
AMIs & Containers
GPUs &
CPUs
Elastic
Inference
Inferentia FPGA
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Comprehend
+Medical
AI SERVICES
ML SERVICES
ML FRAMEWORKS & INFRASTRUCTURE
Amazon
Textract
Amazon
Kendra
Contact Lens
For Amazon Connect
SageMaker Studio IDE
Amazon
CodeGuru
Amazon
SageMaker
DeepGraphLibrary
Amazon
Fraud Detector
Amazon
Translate
The AWS ML Stack
Broadest and most complete set of machine learning capabilities

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VISION SPEECH TEXT SEARCH CHATBOTS PERSONALIZATION FORECASTING FRAUD DEVELOPMENT
CONTACT
CENTERS
Ground
Truth
AWS Marketplace
for ML
Neo
Augmented
AI
Built-in
algorithms
Notebooks Experiments Processing
Model training
and tuning
Debugger Autopilot
Model
hosting
Model
Monitor
Deep Learning
AMIs & Containers
GPUs &
CPUs
Elastic
Inference
Inferentia FPGA
Amazon
Rekognition
Amazon
Polly
Amazon
Transcribe
+Medical
Amazon
Lex
Amazon
Personalize
Amazon
Forecast
Amazon
Comprehend
+Medical
AI SERVICES
ML SERVICES
ML FRAMEWORKS & INFRASTRUCTURE
Amazon
Textract
Amazon
Kendra
Contact Lens
For Amazon Connect
SageMaker Studio IDE
Amazon
CodeGuru
Amazon
SageMaker
DeepGraphLibrary
Amazon
Fraud Detector
Amazon
Translate
The AWS ML Stack
Broadest and most complete set of machine learning capabilities

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Personalizing the
driving experience
Kia Motors uses Amazon Rekognition for advanced
image and video analysis of an in-car camera that
detects the driver. Then, the car automatically
adjusts driver-assistance features like personalized
mirror and seat positioning.

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Real-time
identity verification
Aella Credit uses Amazon Rekognition to
analyze images to verify an individual’s
identity in real-time without human
intervention, allowing it to provide instant
loans to eligible customers through its mobile
app.

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ML based computer vision
helps insurance provider
nib, uses Amazon Textract to help 1.6 million
Australian and New Zealand residents by
going beyond their traditional OCR tooling to
speed up claims processing, resulting in a
great customer experience while increasing
their operational efficiencies.

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Amazon Rekognition:
Deep-Learning-Based Image and Video Analysis

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Video
Amazon Rekognition applies machine learning
to extract information from images and video
Images

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Amazon Rekognition Features
Faces Celebrities Labels
Moderation ScenesActivities Paths
Text

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Amazon Rekognition Benefits
Low cost
Your data
is your ownServerless
Rapid
integration
State of the
art capabilities
Continuous
improvement

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Media discovery
Customer
engagement Industrial
… and more
Safe content Public safety Mapping
Amazon Rekognition Customers

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Amazon Rekognition Customers

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Object and scene detection

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Object and scene detection

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Object and scene detection

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Custom Labels

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Custom Labels
Torque Converter

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Custom Labels
Torque Converter

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Custom Labels
Torque Converter
HANDS-ON DEMO

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Activities and paths

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Text in the wild

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Make the design match
Top-level
category
Second-level
category
Confidence
score
Explicit nudity
Nudity XX.X%
Graphic male nudity XX.X%
Graphic female nudity XX.X%
Sexual activity XX.X%
Partial nudity XX.X%
Suggestive
Female swimwear
or underwear
XX.X%
Male swimwear
or underwear
XX.X%
Revealing clothes XX.X%
Rekognition for Content Moderation

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Celebrity detection

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Face – Common Use Cases
Customer Analysis
Analyze trends, not individuals
Recognize Your Customer
Verify the identities of customers who opt-in

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Recognize your customer
Verify the identities of customers who opt-in

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Face Detection, Analysis, and Recognition
LightingPose Blur and occlusion

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Face – Customer Analysis
With trends, not individually

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Face – Customer Analysis
With trends, not individually

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Face – Customer Analysis
With trends, not individually
HANDS-ON DEMO

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Shot Detection
Color Bars
Ends Credit
Black Frames
Detecting Video Segments

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Shot Detection
Color Bars
Ends Credit
Black Frames
Detecting Video Segments
HANDS-ON DEMO

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Documents are a Primary Business Tool Across Industries
Finance
Insurance
Real estate
Accounting
Tax management
Medical
Legal
Business management
Education
And many more…

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Amazon Confidential
How Documents are Processed Today
Manual
processing
Rules and
template-based extraction
Optical Character
Recognition (OCR)
• Expensive
• Error Prone
• Time Consuming
• Simple Documents Only
• Error Prone
• Flat Bag of Words
• Limited by Accuracy of OCR
• Dev and Management Overhead
• Templates are Brittle

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Amazon Confidential
Benefits of Amazon Textract

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Amazon Confidential
Amazon Textract Features
Text extraction Table extraction Form extraction Human in the
Loop (A2i)

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Amazon Confidential
Text Extraction
Blocks: PAGE, LINE, WORD
is washed by waves, and cooled

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Amazon Textract –
Text Extraction simplified
Output
Extract data quickly &
accurately
No code or templates to
maintain

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Amazon Confidential
Table Extraction
Blocks: PAGE, TABLE, CELL
For each ’block’ you get:
• Text
• Confidence score
• Block relationships (e.g. cells within a table)

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Output {
Start Date: 1/15/2009
End Date: 6/30/2013
Employer Name: Any Company
Position Held: Head Baker
Reason for leaving: Family relocated
}
Amazon Textract –
Table Extraction simplified

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Amazon Confidential
Form Extraction
Blocks: PAGE, KEY_VALUE_SET
For each ’block’ of your document:
• Form field name (key) and field value (value) association
• Confidence score
• Page number
• Block relationships

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Output Full Name:
First: John
Middle: X
Last: Doe
Date of Birth:
MM: 01
DD: 01
YYYY: 1971
Gender:
Male: True
Female: False
Amazon Textract –
Form Extraction simplified

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Supports single-page
documents such
as images (e.g.,
mobile capture)
For multi-page documents,
up to 3,000 pages
Amazon Textract
Sync and Async APIs

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• Regulatory requirements
• Sensitive decisions
(e.g. issuing a loan)
• Hard-to-read documents
• …more
Human review makes it
easier for some customers
to adopt AI
Textract works with Amazon A2i for human review

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Textract works with Amazon A2i for human review
Client application
sends documents to
Amazon Textract
Amazon Textract
extracts text and
structured data from
scanned documents
Results stored
to Amazon S3
1 2
6
4 Low-confidence
predictions sent for human
review
3
High-confidence predictions
returned immediately to client
application
5 Reviews consolidated
using Amazon A2I answer
consolidation algorithms
Client
application

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• Problem: Review medical prescription documents and issue
payments to pharmacists quickly and accurately. Human
involvement mandatory, but NHS wants to take advantage of
AI.
• Benefit of Textract and A2I: “Amazon Textract is compelling
because it offers AI powered extraction of text and structured
data from virtually any document. We are excited about A2I
because it allows us to take advantage of ML while still
applying human judgement. That’s a game changer for us.”

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Textract Partner Ecosystem
Consulting(SI)PartnersPlatform(ISV)

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How to start
Test on AWS console UI
https://github.com/aws-samples
https://www.amazonaws.cn/en/solutions

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Thanks!