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A Novel Content Detection Approach for Handwritten English letters

机译:一种新的手写英语字母内容检测方法

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The rise of Artificial Intelligence technology along with machine and deep learning are opening up almost limitless possibilities. There is also an element of fear towards this exponential growth. But it’s the humanization of our machines and devices that is seldom discussed or reported. But we deem it acceptable to nominate an unfortunate volunteer to retype notes scribbled on tiny pieces of paper so they can send to other attendees. Once again we need to ask ourselves if this is the most efficient method of managing our workload in this digital age. In order to solve this problem, we are proposing a solution to solve this. Instead of predicting by word, here we will be segregating the cursive English letter to individual characters and predicting it via trained Convolutional Neural Network (CNN) model. By using this methodology, increase in rate of prediction of the individual characters is been increased and it could be implemented to digitalize the forms in companies which will be a greater level of automation.
机译:人工智能技术的兴起以及机器和深度学习正在开放几乎无限的可能性。还有一个对这种指数增长的恐惧的要素。但这是我们很少讨论或报道的机器和设备的人性化。但是,我们认为,提名一个不幸的志愿者在微小的纸上涂上涂抹的纸张,所以可以发布到其他与会者。我们再次需要询问自己,如果这是在这个数字时代管理我们工作量的最有效方法。为了解决这个问题,我们建议解决这个问题。在这里,我们将通过培训的卷积神经网络(CNN)模型来将草图英语字母分离并通过培训的卷积神经网络(CNN)模型来分离法学英语字母。通过使用这种方法,增加了各个字符的预测率的增加,可以实施,以数字化将成为更大水平自动化的公司的形式。

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