SEAL : DATA DE-IDENTIFICATION SOLUTION FOR ALL
SEAL data de-identification solution enables you to use the data without privacy concerns. It perfectly removes Personal Information from the data while preserving its visual information and utilities for AI training. SEAL de-identified data is safe to use and innovate your AI. Make big data of your business and train AI safely with SEAL.
WHY IS SEAL SUPERIOR TO OTHER DE-IDENTIFICATIONS?
AI trained with SEAL
AI model trained with SEAL-ed data shows negligible accuracy drop
AI trained with blur
AI trained with blurred (mosaic, mask, etc.) images 1. Regards blurred areas as faces 2. Fails to detect a person with clear pixels of face Low value as a training dataset, Known to have issues in industry
TRAIN AI SAFELY, WITHOUT ACCURACY-DROP
AI models trained with SEALed data preserve the accuracy of the original.
Other de-identification methods significantly lose AI quality.
* The results of learning a pedestrian detection model using an open-source dataset * mAP : mean Average Precision
SEAL INNOVATES YOUR AI TRAINING INFINITELY
*Base model : Trained with 30K RGB *Base model + Seal-ed data : Trained with 30K RGB + 30K SEAL-ed image
Base model + SEAL-ed data
Target Scope : Pedestrian Detection Base Model : YOLOv5
01 AUTONOMOUS DRIVING
Safeguarding datasets to develop person and vehicle detection AI models for autonomous driving solutions
Improving model accuracy by training on anonymous data collected in real-world settings, as opposed to open-source data.
02 DATA FOR VEHICLE BLACK BOX VIDEO
Securing incident videos from the vehicle’s black box without privacy concerns
Calculating the compensation ratio and developing AI video analytics by using the vehicle’s black box video data
03 LARGE-SCALE DATA AI TRAINING
Removing personal information for government-level AI data projects
Preserving ML trainability with SEAL to achieve higher-accuracy models compared to those trained on standard blurred data.
SPEAK TO A SEAL EXPERT
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With SEAL, private information such as license plates and pedestrians’ faces can be anonymized even in videos obtained from moving cameras