Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Current computer vision systems whose basic methodology is open-loop or filter type typically use image segmentation follod by object recognition algorithms. These systems are not robust for most real-world applications. In contrast, the system presented here achieves robust performance by using reinforcement learning to induce a mapping from input images to corresponding segmentation parameters. This is accomplished by using the confidence level of model matching as a reinforcement signal for a team of learning automata to search for segmentation parameters during training. The use of the recognition algorithm as part of the evaluation function for image segmentation gives rise to significant improvement of the system performance by automatic generation of recognition strategies. The system is verified through experiments on sequences of color images with varying external conditions.
['Jing Peng', 'Bir Bhanu']
I am writing a research paper on a idea Closed-loop object recognition using reinforcement learning
[{"from": "human", "value": "I am writing a research paper on a idea Closed-loop object recognition using reinforcement learning"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Current computer vision systems whose basic methodology is open-loop or filter type typically use image segmentation follod by object recognition algorithms. These systems are not robust for most real-world applications. In contrast, the system presented here achieves robust performance by using reinforcement learning to induce a mapping from input images to corresponding segmentation parameters. This is accomplished by using the confidence level of model matching as a reinforcement signal for a team of learning automata to search for segmentation parameters during training. The use of the recognition algorithm as part of the evaluation function for image segmentation gives rise to significant improvement of the system performance by automatic generation of recognition strategies. The system is verified through experiments on sequences of color images with varying external conditions."}]