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Method and apparatus for conserving computing resources required in the process of verifying the integrity of convolution parameters using a test pattern and improving defect tolerance and swing robustness in extreme situations

机译:节省在使用测试模式验证卷积参数完整性并提高极端情况下的缺陷容忍度和挥杆鲁棒性过程中所需的计算资源的方法和设备

摘要

PROBLEM TO BE SOLVED: To save the computing resource required in the process of verifying the integrity of a convolution parameter using a test pattern. A background prediction unit is obtained when information about the (t-2)th image and the (t-1)th image corresponding to the (t-i2)th frame and the (t-i1)th frame of an image is obtained. , The information about the (t−2)th image and the (t−1)th image is referred to, the tth background prediction information of the tth image is generated, and when the tth image is acquired, the pattern insertion unit, With reference to the t-th background prediction information, a test pattern is inserted into the t-th image to generate a verification input, and a neural network is used to apply a convolution operation to the verification input to generate a verification output. The verification unit references the verification output and the reference output corresponding to the test pattern to determine the integrity of the neural network. [Selection diagram] Figure 2
机译:要解决的问题:在使用测试模式验证卷积参数完整性的过程中,节省所需的计算资源。当获得关于与图像的第(t-i2)帧和第(t-i1)帧相对应的第(t-2)个图像和第(t-1)个图像的信息时,获得背景预测单元。参照关于第(t-2)个图像和第(t-1)个图像的信息,生成第t个图像的第t个背景预测信息,并且当获取第t个图像时,图案插入单元,参考第t个背景预测信息,将测试图案插入第t个图像中以生成验证输入,并且使用神经网络将卷积运算应用于验证输入以生成验证输出。验证单元参考验证输出和与测试模式相对应的参考输出,以确定神经网络的完整性。 [选择图]图2

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