Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents our methods for the tasks of bilingual ad hoc retrieval and automatic annotation in ImageCLEF 2005. In ad hoc task,  propose a feedback method for cross-media translation in a visual run, and combine the results of visual and textual runs to generate the final result. Experimental results show that our feedback method performs ll. Comparing to initial visual retrieval, average precision is increased from 8% to 34% after feedback. The performance is increased to 39% if  combine the results of textual run and visual run with pseudo relevance feedback. In automatic annotation task,  propose several methods to measure the similarity beten a test image and a category, and a test image is classified to the most similar category. Experimental results show that the proposed approaches have good performance, but the simplest 1-NN method has the best performance.  will analyze these results in the paper.
['Yih-Cheng Chang', 'Wen-Cheng Lin', 'Hsin-Hsi Chen']
I am writing a research paper on a idea Combining Text and Image Queries at ImageCLEF2005
[{"from": "human", "value": "I am writing a research paper on a idea Combining Text and Image Queries at ImageCLEF2005"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents our methods for the tasks of bilingual ad hoc retrieval and automatic annotation in ImageCLEF 2005. In ad hoc task,  propose a feedback method for cross-media translation in a visual run, and combine the results of visual and textual runs to generate the final result. Experimental results show that our feedback method performs ll. Comparing to initial visual retrieval, average precision is increased from 8% to 34% after feedback. The performance is increased to 39% if  combine the results of textual run and visual run with pseudo relevance feedback. In automatic annotation task,  propose several methods to measure the similarity beten a test image and a category, and a test image is classified to the most similar category. Experimental results show that the proposed approaches have good performance, but the simplest 1-NN method has the best performance.  will analyze these results in the paper."}]