Abstract :
Multimedia technologies represent new ground for research interactions among a variety of media such as speech, audio, image, video, text, and graphics. Future multimedia technologies will need to handle information a with an increasing level of intelligence, i.e., automatic recognition and interpretation of multimodal signals. The main attribute of neural processing is its adaptive learning capability, which enables machines to be taught to interpret possible variations of a same object or pattern, e.g. scale, orientation, and perspective. Moreover, we are able to accurately approximate unknown systems based on sparse sets of noisy data. In addition, spatial/temporal neural structures and hierarchical models are promising for multirate, multiresolution multimedia processing
Keywords :
adaptive systems; learning (artificial intelligence); multimedia communication; neural nets; signal processing; adaptive learning; audio; automatic signal interpretation; automatic signal recognition; graphics; hierarchical models; image; intelligent multimedia processing; multimedia technologies; multimodal signals; multirate processing; multiresolution multimedia processing; neural networks; neural processing; noisy data; orientation; scale; spatial/temporal neural structures; speech; text; video; Artificial neural networks; Content based retrieval; Face detection; IEEE Press; Indexing; Intelligent networks; MPEG 7 Standard; Neural networks; Pattern recognition; Speech;