Download Machine Learning for Audio, Image and Video Analysis: Theory by Francesco Camastra PhD, Alessandro Vinciarelli PhD (auth.) PDF

By Francesco Camastra PhD, Alessandro Vinciarelli PhD (auth.)

Machine studying includes a number of clinical domain names together with arithmetic, computing device technological know-how, information and biology, and is an procedure that permits pcs to instantly examine from facts. targeting complicated media and the way to transform uncooked facts into worthy info, this ebook deals either introductory and complicated fabric within the mixed fields of computing device studying and image/video processing.

The computer studying options offered permit readers to deal with many genuine global difficulties concerning complicated information. Examples protecting parts comparable to automated speech and handwriting transcription, computerized face attractiveness, and semantic video segmentation are incorporated, besides special introductions to algorithms and examples in their functions.

The ebook is equipped in 4 components: the 1st makes a speciality of technical points, easy mathematical notions and ordinary computer studying options. the second one offers an intensive survey of such a lot appropriate laptop studying suggestions for media processing, whereas the 3rd half specializes in purposes and indicates how concepts are utilized in real difficulties. The fourth half includes designated appendices that supply notions in regards to the major mathematical tools used during the text.

Students and researchers wanting a pretty good starting place or reference, and practitioners attracted to getting to know extra in regards to the state of the art will locate this e-book worthy. Examples and difficulties are in line with info and software program programs publicly to be had at the web.

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Extra info for Machine Learning for Audio, Image and Video Analysis: Theory and Applications

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4 provides a description of the main psychoacoustic phenomena used in mp3. 3 AAC Digital Audio Coding The acronym AAC stands for advanced audio coding and the corresponding encoding technique is considered as the natural successor of the mp3 (see the previous section) [29]. The structures of mp3 and AAC are similar, but the latter improves some of the algorithms included in the different layers. AAC contains two major improvements with respect to mp3. The first is the higher adaptivity with respect to the characteristics of the audio.

4) The equations of this section assume that an acoustic wave is completely characterized by two parameters: the frequency f and the amplitude A. From a perceptual point of view, A is related to the loudness and f corresponds to the pitch. While two sounds with equal loudness can be distinguished based on their frequency, for a given frequency, two sounds with different amplitude are perceived as the same sound with different loudness. e. the number of cycles per second. The measurement of A is performed through the physical effects that depend on the amplitude like pressure variations.

The nerves connected to the external cochlea walls in correspondence of such a point are excited and the information about the presence of f is transmitted to the brain. The frequency-to-place conversion is modeled in some popular speech processing algorithms through the critical band analysis. e. 2 0 Bark Scale Mel Scale 0 1000 2000 3000 4000 frequency (Hz) 5000 6000 7000 8000 Fig. 4. Frequency normalization. Uniform sampling on the vertical axis induces on the horizontal axis frequency intervals more plausible from a perceptual point of view.

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