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What is Satim?
Satim delivers a remarkable AI-powered software solution that excels in identifying, categorizing, and recognizing objects by utilizing Synthetic Aperture Radar (SAR) satellite imagery. The firm has created an advanced simulator that can produce synthetic SAR signatures, allowing for the generation of signatures for any object and any SAR system. This groundbreaking simulator enables us to introduce various new object types for training our AI models, achieving impressive classification accuracy rates of 90% within just a few days. Thanks to our innovative SAR data simulator, the models can swiftly adapt to recognize and classify newly emerging objects, providing essential flexibility to tackle the ever-evolving challenges encountered by military, government, and commercial sectors. Our collaborations with leading SAR sensor manufacturers help us combine state-of-the-art technology with unparalleled expertise in the field. Moreover, our vast international network of partners is committed to driving progress in the space and defense sectors, ensuring that we stay ahead of the curve in innovation. By working together, we aspire to continuously redefine the possibilities within object detection and classification, ultimately enhancing operational effectiveness and safety across various industries. This collaborative effort reinforces our mission to lead the charge in advancing cutting-edge solutions for the future.
What is Amazon Rekognition?
Amazon Rekognition streamlines the process of incorporating image and video analysis into applications by leveraging robust, scalable deep learning technologies, which require no prior machine learning expertise from users. This advanced tool is capable of detecting a wide array of elements, including objects, people, text, scenes, and activities in both images and videos, as well as identifying inappropriate content. Additionally, it provides accurate facial analysis and search capabilities, making it suitable for various applications such as user authentication, crowd surveillance, and enhancing public safety measures.
Furthermore, the Amazon Rekognition Custom Labels feature empowers businesses to identify specific objects and scenes in images that align with their unique operational needs. For example, a company could design a model to recognize distinct machine parts on an assembly line or monitor plant health effectively. One of the standout features of Amazon Rekognition Custom Labels is its ability to manage the intricacies of model development, allowing users with no machine learning background to successfully implement this technology. This accessibility broadens the potential for diverse industries to leverage the advantages of image analysis while avoiding the steep learning curve typically linked to machine learning processes. As a result, organizations can innovate and optimize their operations with greater ease and efficiency.
Integrations Supported
AWS AI Services
AWS App Mesh
Amazon Augmented AI (A2I)
Amazon Web Services (AWS)
BotCore
Descope
Orange Logic OrangeDAM
Qrvey
Quickwork
Trendzact
Integrations Supported
AWS AI Services
AWS App Mesh
Amazon Augmented AI (A2I)
Amazon Web Services (AWS)
BotCore
Descope
Orange Logic OrangeDAM
Qrvey
Quickwork
Trendzact
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Satim
Date Founded
2012
Company Location
Poland
Company Website
satim.co
Company Facts
Organization Name
Amazon
Date Founded
1994
Company Location
United States
Company Website
aws.amazon.com/rekognition/
Categories and Features
Categories and Features
Computer Vision
Blob Detection & Analysis
Building Tools
Image Processing
Multiple Image Type Support
Reporting / Analytics Integration
Smart Camera Integration
Content Moderation
Artificial Intelligence
Audio Moderation
Brand Moderation
Comment Moderation
Customizable Filters
Image Moderation
Moderation by Humans
Reporting / Analytics
Social Media Moderation
User-Generated Content (UGC) Moderation
Video Moderation
Deep Learning
Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization
Emotion Recognition
Facial Emotions
Facial Expression Analysis
Machine Learning
Photo Emotions
Speech Emotions
Video Emotions
Written Text Emotions
OCR
Batch Processing
Convert to PDF
ID Scanning
Image Pre-processing
Indexing
Metadata Extraction
Multi-Language
Multiple Output Formats
Text Editor
Zone Selection Tool
People Counting
API
Anonymous Counting
Benchmarking
Car Counting
Conversion Tracking
Data Export
Events Statistics
Heatmaps
Mood/Age/Gender Recognition
Motion Detection
Reporting / Analytics
Retail Counting
Staff Exclusion
WiFi Tracking
Zone / Area Monitoring
Session Replay
Eye Tracking
Form Analytics
Heatmaps
Mouse Tracking
Optimization Tools
Session Recording
Surveys
User Experience Analysis
User Feedback
Visitor Segmentation
