Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the rapid development of technologies for fast access to the Internet and the popularization of digital cameras, enormous digital images are posted and shared online everyday. Simultaneously, b images are usually organized by topics of events and are often assigned appropriate topic-related text descriptions. Given a set of images along with corresponding texts, a challenging problem is how to utilize the available information to perform image retrieval tasks, such as image classification and image clustering. Previous works on image categorization focus on either adopting text or image features, or simply combining these two types of information together. ,  propose two novel approaches (Dynamic ighting and Region-based Semantic Concept Integration) to categorize the images under the “supervision” of topic-related text descriptions; In addition,  provide a comparative experimental investigation on utilizing text and image information to tackle image classification. Empirical experiments on a manually collected image dataset (consisting of images related to the events after disasters) demonstrate the efficacy of our proposed classification methods.
['Lei Li', 'Wenting Lu', 'Jingxuan Li', 'Tao Li', 'Honggang Zhang', 'Jun Guo']
I am writing a research paper on a idea Exploring Interaction Between Images and Texts for Web Image Categorization
[{"from": "human", "value": "I am writing a research paper on a idea Exploring Interaction Between Images and Texts for Web Image Categorization"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: With the rapid development of technologies for fast access to the Internet and the popularization of digital cameras, enormous digital images are posted and shared online everyday. Simultaneously, b images are usually organized by topics of events and are often assigned appropriate topic-related text descriptions. Given a set of images along with corresponding texts, a challenging problem is how to utilize the available information to perform image retrieval tasks, such as image classification and image clustering. Previous works on image categorization focus on either adopting text or image features, or simply combining these two types of information together. ,  propose two novel approaches (Dynamic ighting and Region-based Semantic Concept Integration) to categorize the images under the \u201csupervision\u201d of topic-related text descriptions; In addition,  provide a comparative experimental investigation on utilizing text and image information to tackle image classification. Empirical experiments on a manually collected image dataset (consisting of images related to the events after disasters) demonstrate the efficacy of our proposed classification methods."}]