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Nowadays, viewers find it really hard to watch what they prefer easily because of the increasingly huge number of television channels. Given this problem, we will try to work on the concept of intelligent television and we propose to add an intelligent layer, that can be configured according to user preferences in order to make them suitable for many video analysis at the same time, and filter for...
Televisions and spatial channels have invaded wealthy and poor families. With the growing number of TV channels, the TV viewers become unable to watch what they prefer easily. They will be obliged to zap between thousands of channels permanently to have the right program. With the apparition of DTT (Digital Terrestrial Television), it will be possible for televisions of next generations to receive...
The paper proposes a novel semi-automatic soft collaborative annotation scheme for video semantic indexing. To annotate video data effectively and accurately, a video collaborative soft annotation within users' judgment modeling is first proposed in this paper. We, then, introduce a semiautomatic annotation strategy which combines the active learning and self-training in order to reduce the annotators'...
In this paper, we propose a new linguistic-based approach called the affixal approach for Arabic word and text image recognition. Most of the existing works in the field integrate the knowledge of the Arabic language in the recognition process in two ways: either in post-recognition using the language of dictionary (dictionary of words) to validate the word hypotheses suggested by the OCR or in the...
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