Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear models to image patch histograms.  show that it works ll on three tasks and performs significantly better than other methods using the same features. For example, the method decides that patches containing an eye are most important for distinguishing face from background images. The recognition performance is very competitive with error rates presented in other publications. In particular, a new best error rate for the Caltech motorbikes data of 1.5% is achieved.
['Thomas Deselaers', 'Daniel Keysers', 'Hermann Ney']
I am writing a research paper on a idea Discriminative training for object recognition using image patches
[{"from": "human", "value": "I am writing a research paper on a idea Discriminative training for object recognition using image patches"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  present a method for automatically learning discriminative image patches for the recognition of given object classes. The approach applies discriminative training of log-linear models to image patch histograms.  show that it works ll on three tasks and performs significantly better than other methods using the same features. For example, the method decides that patches containing an eye are most important for distinguishing face from background images. The recognition performance is very competitive with error rates presented in other publications. In particular, a new best error rate for the Caltech motorbikes data of 1.5% is achieved."}]