ID 原文 译文
40966 该方法利用梯度计算进行区间定位，计算输入曲线的不同位置对攻击成功的影响程度，从而可以准确地定位输入曲线的泄露区间。 This method applies gradient mapping to compute the attacking effectiveness of different positions on the input trace.According to the attacking effectiveness, the leakage position of the input trace can be precisely located.
40967 通过实验对比其他常见的可视化方法在模板攻击中的应用效果，发现其拥有曲线平滑和噪音小的优势。 The experiment shows that this new method has advantages of smooth result and lower noise, compared with other common visualization methods.
40968 实验证明在泄露情况未知且不进行二阶曲线处理的情况下，即使网络成功率较低，也可以直接对带掩码实现的曲线进行精准定位。 The result shows that this attack method can be used to localize the masked implementations precisely, without leakages combination processing and without knowledge of the implemented protections, even on the condition of low successful rate.
40969 针对基于卷积神经网络的视频插帧算法模型参数过大、实时性差、内存占用高、难以广泛应用的问题，提出了一种基于双向光流和多尺度特征融合的轻量级级联推理网络模型。 Aiming at the problems that the model parameters of video interpolation algorithm based on convolutional neural network are too large, poor real-time, high memory occupation and difficult to be widely used, a lightweight cascading inference based on bidirectional optical flow and multi-scale feature fusion is proposed.
40970 将视频插帧任务分解为帧间运动合成和纹理重建两个步骤，设计了一种轻量级的级联双向光流预测网络，并提出了一种多尺度空间与纹理特征融合网络模型，实现了对视频帧多尺度纹理特征和复杂运动特征的充分提取和利用。 The network model decomposes the task of video frame insertion into two steps of inter-frame motion synthesis and texture reconstruction, designs a lightweight two-way optical flow prediction network, and proposes a multi-scale spatial and texture feature fusion network model.The multi-scale texture features and complex motion features of video frames are fully extracted and utilized.
40971 该模型使用相邻的两个视频帧和所需中间帧的位置作为网络输入，首先计算两个输入帧的空间金字塔特征与纹理金字塔特征; The model uses the position of two adjacent video frames and the required intermediate frames as network inputs.First, the spatial pyramid features and texture pyramid features of the two input frames are calculated.
40972 然后使用空间金字塔特征计算帧间的多尺度双向光流; Then the spatial pyramid features are used to calculate the multi-scale bidirectional optical flow between frames, meanwhile, calculating the spatial and texture features of the intermediate frame.
40973 随后结合双向光流，计算出中间帧的空间特征和纹理特征; Finally, a fusing network is introduced to generate the multi-scale space and texture features of the intermediate frame to generate the final required video frame.
40974 最后融合中间帧的多尺度空间、纹理特征得到最终所需的视频帧。在Vimeo90K和UCF101数据集上的实验表明，在保证精度的前提下，本文算法在计算速度和模型参数量上具有更好的表现。 Experiments on the Vimeo90 K and UCF101 datasets show that, under the premise of guaranteeing accuracy, the algorithm in this paper has better performance in terms of calculation speed and model parameters.
40975 为克服传统图像增强算法在光照强度不均的密闭腔体内对图像增强不足和自然度保留能力弱的问题，本文提出了一种双曝光度图像融合的算法。 To overcome the problem of insufficient enhancement and weak naturalness preservation ability of the image in a closed cavity with uneven illumination intensity, a double exposure image fusion algorithm is proposed in this paper.