Powerup’s deep understanding of image processing and object recognition technologies have helped many organizations automate their image moderation processes.
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Science Behind Image Recognition
Image recognition usually covers a wide range of use cases from identifying a human face, objects, texts, scenes, activities, screen inappropriate content, etc. Powerup has built several image analysis AI solutions which integrate with Microsoft Computer Vision, Amazon Rekognition, Google Cloud Vision, etc.
We help extract rich information from images to identify, categorize and process visual data. Our strong image pre-processing techniques combined with deep learning enabled image data extraction helps you prepare for further analysis.
Popular Image Recognition Use Cases
Image Analysis in Aircraft Inspection
Image Analysis for Roller Coaster Safety
Image Analysis for Photo Moderation
Powerup AI Solution Development
Framework (PASDF)
Step 1
Identify the data sources and define the AI solution approach
Step 2
Collate the data in data lake for further processing
Step 3
Develop and implement the AI solution workflow and ml engine for accuracy tuning
Step 4
Open for user testing and conduct security & load testing
Step 5
Go-live with continuous support for further accuracy improvement
Face Recognition (FR)
- Trains the algorithm for face recognition using training dataset which requires at least 3 snaps of the face.
- Uses the industry-leading face recognition coordination metrics to detect the face from the large pool of faces database.
- Ranks the matching faces based on confident score and select the top-rated face as output.
Object Recognition (OR)
- Identifies various objects from the image including most of the natural and man-made objects.
- Our Object Recognition algorithms come with video pre-processing capabilities, detecting objects in the video.
- The identified objects are processed further and get consumed in specific use cases.
OCR (Optical Character Recognition)
- Detect text in an image using optical character recognition (OCR) and extract the recognized words into a machine-readable character stream.
- Analyze images to detect embedded text, generate character streams, and enable searching.
- Push the extracted data set for further processing and implement end-to-end automation in relevant use cases.
ICR (Intelligent Character Recognition)
- Detect and extract handwritten text from notes, letters, essays, whiteboards, forms, and other sources.
- Comprehend data quickly from ICR & OCR extract for further analysis of large data sets.
- Push the extracted data set for further processing and implement end-to-end automation in relevant use cases.
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