EmotionPlayer: Cutting-Edge Sentiment and Content Analysis for Media
Problem and implemented solution
With the explosion of media content, manual moderation and sentiment analysis are inefficient and error-prone. EmotionPlayer effectively automates media sentiment recognition and content classification.
Nomination
Artificial Intelligence And Digital Services
Topic
Artificial intelligence
Estimated duration of implementation
12-16 months
Implementation geography
EmotionPlayer can be implemented globally, with no specific regional restrictions, making it suitable for use in any locale where video content analysis is needed.
Description of competitive advantages
EmotionPlayer stands out with its pure C implementation for optimal performance, multithreading support for efficient processing, seamless C# integration, and real-time progress tracking, making it a robust and versatile solution for media sentiment and content analysis.
List of awards and prizes, media articles about the organization/individual or the Practice
RUKAMI Fest, winner - https://www.vesti.ru/nauka/article/2488130; VDNH RUSSIA 2023-2024 Member; Junior ML Contest - 2022 winner; Junior ML Contest - 2023 winner - https://ods.ai/tasks/junior-ml-contest
List of scientific works and IP connected with the Practice
Software № 2023669387 from 14.09.2023, Software № 2023660141 from 18.05.2023
