计算机科学 ›› 2020, Vol. 47 ›› Issue (6A): 166-171.doi: 10.11896/JsJkx.190600179
吴昊昊, 王方石
WU Hao-hao and WANG Fang-shi
摘要: 在采用深度学习进行图像分类时,为减少下采样导致的空间信息损失,往往采用膨胀卷积代替下采样,但尚未有文献研究膨胀卷积作用于不同网络层的性能差异。文中进行了大量图像分类实验,找到了适宜膨胀卷积作用的最佳网络层。 但使用膨胀卷积会丢失近邻点的相关信息,导致网格现象,造成图像部分局部信息的丢失。为消除网格现象,又提出在前述最佳网络层采用多尺度膨胀卷积构建神经网络的方法。实验结果表明,所提出的构建网络方法在图像分类中取得了较好的效果。
中图分类号:
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