Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In machine vision, Scale-invariant feature transform (SIFT) and its variants have been widely used in image classification task. How- ever, the high dimensionality nature of SIFT features, usually in the or- der of multiple thousands per image, would require careful consideration in place to achieve accurate and timely categorization of objects within images.  explores the possibility of processing SIFT features as tensors and uses tensor decomposition techniques on high-order SIFT tensors for dimensionality reduction. The method focuses on both accu- racy and efficiency aspects and the validation result with the Caltech 101 dataset confirms the improvement with notable margins.
['Tan Vo', 'Dat Tran', 'Wanli Ma']
I am writing a research paper on a idea Tensor Decomposition of Dense SIFT Descriptors in Object Recognition
[{"from": "human", "value": "I am writing a research paper on a idea Tensor Decomposition of Dense SIFT Descriptors in Object Recognition"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In machine vision, Scale-invariant feature transform (SIFT) and its variants have been widely used in image classification task. How- ever, the high dimensionality nature of SIFT features, usually in the or- der of multiple thousands per image, would require careful consideration in place to achieve accurate and timely categorization of objects within images.  explores the possibility of processing SIFT features as tensors and uses tensor decomposition techniques on high-order SIFT tensors for dimensionality reduction. The method focuses on both accu- racy and efficiency aspects and the validation result with the Caltech 101 dataset confirms the improvement with notable margins."}]