Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The ImageCLEF 2012 Scalable Image Annotation Using Gen- eral b Data Task proposed a challenge, in which as training data instead of relying only on a set of manually annotated images, the ob- jective was to make use of automatically gathered b data, with the aim of developing more scalable image annotation systems. To this end, the participants re provided with a new dataset, composed of 250,000 images for training, which included various visual feature types, and tex- tual features obtained from the bsites in which the images appeared. Two subtasks re defined. The first subtask employed the same test set as the ImageCLEF 2012 Flickr Photo Annotation subtask, with the particularity that both the Flickr and b training sets had to be used. The idea was to determine if the b data could help to enhance the annotation performance in comparison to using only manually annotated data. The second subtask consisted in using only automatically gathered b data to develop an image annotation system. For this,  provided a development and test sets of 1,000 and 2,000 images, respectively, both manually annotated for 95 and 105 concepts, respectively. The partici- pants of the first subtask re not able to take advantage of the b data to enhance the annotation performance. On the contrary, in the second subtask interesting results re obtained. As expected, the over- all performance of the systems is worse than using manually annotated data, nonetheless, the results are promising when analyzing per concept. For some concepts the performance is relatively good, confirming that the b data can in fact be quite useful. Moreover, due to the low par- ticipation and the relatively simple techniques used, it is believed that there is considerable room for improvement on both subtasks.
['Mauricio Villegas', 'Roberto Paredes']
I am writing a research paper on a idea Overview of the ImageCLEF 2012 Scalable Web Image Annotation Task
[{"from": "human", "value": "I am writing a research paper on a idea Overview of the ImageCLEF 2012 Scalable Web Image Annotation Task"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: The ImageCLEF 2012 Scalable Image Annotation Using Gen- eral b Data Task proposed a challenge, in which as training data instead of relying only on a set of manually annotated images, the ob- jective was to make use of automatically gathered b data, with the aim of developing more scalable image annotation systems. To this end, the participants re provided with a new dataset, composed of 250,000 images for training, which included various visual feature types, and tex- tual features obtained from the bsites in which the images appeared. Two subtasks re defined. The first subtask employed the same test set as the ImageCLEF 2012 Flickr Photo Annotation subtask, with the particularity that both the Flickr and b training sets had to be used. The idea was to determine if the b data could help to enhance the annotation performance in comparison to using only manually annotated data. The second subtask consisted in using only automatically gathered b data to develop an image annotation system. For this,  provided a development and test sets of 1,000 and 2,000 images, respectively, both manually annotated for 95 and 105 concepts, respectively. The partici- pants of the first subtask re not able to take advantage of the b data to enhance the annotation performance. On the contrary, in the second subtask interesting results re obtained. As expected, the over- all performance of the systems is worse than using manually annotated data, nonetheless, the results are promising when analyzing per concept. For some concepts the performance is relatively good, confirming that the b data can in fact be quite useful. Moreover, due to the low par- ticipation and the relatively simple techniques used, it is believed that there is considerable room for improvement on both subtasks."}]