Why NEXTDATA ?
User- insensitive Video Detection
Deeply integrate GAN, TDNN, LSTM, RNN and other models to avoid the natural defects of a single model and create a composite and efficient model system
Omnidirectional Recognition of Content in Videos
A three-level labeling system, which divides labels carefully, makes risk control easy to adapt and easy to adjust
Support the Detection of Various Risky Content
Pornography
Accurately identify pornographic, sexy, vulgar, filthy, pornographic animation, child nudity, game exposure, pornographic videos
Terrorism
Accurately identify bloody riots, terrorist organizations, cult organizations, guns and knives and other violent and terrorist videos in various scenes
Advertisement
Real-time and accurate identification of spam advertisements such as contact information, URLs, QR codes and their variants in various video scenes
Logo Watermark
Voice information containing insults, abuse, slander, etc.
Low-value Content
Accurately identify low-value video content such as empty broadcast, multi-person broadcast, and other negative contents
Minor Identification
Support multiple Voice label identification, through Voice analysis, judge information about children, teenagers and other minors
Custom Content
Support customer-defined sensitive thesaurus, through literal and semantic comprehensive judgment, to filter illegal content in a targeted manner
Support Video Content Recognition in Multiple Scenarios
Quick Access Guide
One-click Application
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Solution Formulation
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API Interface
Test quickly connects to the product for product testing
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