Srilakshmi et al., 2023 - Google Patents
A-DQRBRL: attention based deep Q reinforcement battle royale learning model for sports video classificationSrilakshmi et al., 2023
- Document ID
- 10406110794920910212
- Author
- Srilakshmi G
- Praveen Joe I
- Publication year
- Publication venue
- The Imaging Science Journal
External Links
Snippet
Analyzing video content and classification are the major challenges for computer vision applications. Thus, the proposed research develops a new attention-based deep Q reinforcement battle royale learning (A-DQRBRL) model for effective sports video …
Classifications
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- G06K9/46—Extraction of features or characteristics of the image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06K9/6267—Classification techniques
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- G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
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- G—PHYSICS
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- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00711—Recognising video content, e.g. extracting audiovisual features from movies, extracting representative key-frames, discriminating news vs. sport content
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- G—PHYSICS
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