Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  describe the participation of CNRS TELE- COM ParisTech in the ImageCLEF 2013 Scalable Concept Image Anno- tation challenge. This edition promotes the use of many contextual cues attached to visual contents. Image collections are supplied with visual fea- tures as ll as tags taken from dierent sources (b pages, etc.). Our framework is based on training support vector machines (SVMs) using a class of kernels referred to as context dependent. These kernels are designed by minimizing objective functions mixing visual features and their contextual cues resulting from surrounding tags. The results clearly corroborate the complementarity of tags and visual features and the ef- fectiveness of these context dependent SVMs for image annotation.
['Hichem Sahbi']
I am writing a research paper on a idea CNRS - TELECOM ParisTech at ImageCLEF 2013 Scalable Concept Image Annotation Task: Winning Annotations with Context Dependent SVMs.
[{"from": "human", "value": "I am writing a research paper on a idea CNRS - TELECOM ParisTech at ImageCLEF 2013 Scalable Concept Image Annotation Task: Winning Annotations with Context Dependent SVMs."}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  describe the participation of CNRS TELE- COM ParisTech in the ImageCLEF 2013 Scalable Concept Image Anno- tation challenge. This edition promotes the use of many contextual cues attached to visual contents. Image collections are supplied with visual fea- tures as ll as tags taken from dierent sources (b pages, etc.). Our framework is based on training support vector machines (SVMs) using a class of kernels referred to as context dependent. These kernels are designed by minimizing objective functions mixing visual features and their contextual cues resulting from surrounding tags. The results clearly corroborate the complementarity of tags and visual features and the ef- fectiveness of these context dependent SVMs for image annotation."}]