Fuzzy-controlled perceptual coding of videophone sequences

Leone, A.; Bellini, A.; Guerrieri, R.

doi:10.1109/91.580802

Cited by 5 publications

(2 citation statements)

References 13 publications

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“…Our last case study evaluates the performance of a fuzzy classifier for encoding video sequences, as presented in [23].…”

Section: Fuzzy Classifier For Encoding Video Sequencesmentioning

confidence: 99%

A fuzzy RISC processor

Salapura

2000

IEEE Trans. Fuzzy Syst.

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In this paper, we describe application-specific extensions for fuzzy processing to a general purpose processor. The application-specific instruction set extensions were defined and evaluated using hardware/software codesign techniques. Based on this approach, we have extended the MIPS instruction set architecture with only a few new instructions to significantly speed up fuzzy computation with no increase of the processor cycle time and with only minor increase in chip area. The processor is implemented using a reconfigurable processor core which was designed as a starting point for application-specific processor designs to be used in embedded applications. Performance is presented for three representative applications of varying complexity.Index Terms-Application-specific instruction set, fuzzy processing, fuzzy systems, hardware/software codesign, reconfigurable processor core, subword parallelism.

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“…Our last case study evaluates the performance of a fuzzy classifier for encoding video sequences, as presented in [23].…”

Section: Fuzzy Classifier For Encoding Video Sequencesmentioning

confidence: 99%

A fuzzy RISC processor

Salapura

2000

IEEE Trans. Fuzzy Syst.

View full text Add to dashboard Cite

show abstract

“…Such a system incorporates some linguistic information about the general trends of perceptual relevance (which, for example, is always very low when both activity and entropy are low) and is then adjusted using a reinforcement learning technique taking into account the opinion of a human observer on some test images [4]. With this technique, the human observer only needs to specify whether a proposed relevance coefficient seems OK or is underestimated or overestimated and the preconditions and consequence of the rule which is responsible for the proposal is automatically adjusted [l].…”

Section: Coarse Image Segmentation 22 Pixel Relevance Estimationmentioning

confidence: 99%