We present a new deep learning architecture (called Kd-network) that is designed for 3D model recognition tasks and works with unstructured point clouds. The new architecture performs multiplicative transformations and share parameters of these transformations according to the subdivisions o...
Escape from cells: Deep kd-networks for the recognition of 3d point cloud models. In 2017 IEEE International Conference on Computer Vision (ICCV), pages 863–872. IEEE, 2017 ^Charles Ruizhongtai Qi, Li Yi, Hao Su, and Leonidas J Guibas. Pointnet++: Deep hierarchical feature learning on ...
[31]通过使用一组不平衡的八叉树显著提高了分辨率,其中每个叶节点存储一个汇集的特征表示。Kd-networks[18]以前馈自下而上的方式在具有特定大小的Kd树上计算表示。在Kd网络中,在训练和测试期间,点云中的点的输入数量需要相同,这对于许多任务来说是不成立的。SSCN[7]利用基于体积网格的卷积,通过仅在输入点上考虑...
the scheme of actions, and the application areas. Convolutional neural networks (CNN) are mostly used for image recognition, and rarely for audio recognition. It is mostly applied to images because there is no need to check all the pixels one by one. CNN checks an image...
[55]将知识从以前的网络瞬时转移到新的更深或更广的网络,以加速实验过程。 缺陷:缺基于KD的方法可以使更深的模型变得更浅,显着降低计算成本。 但是KD只能用于具有softmax损失函数的分类任务;另一个缺点是,模型假设有时过于严格,竞争力不够。 其他类型的方法 讨论与挑战...
KD-base 可以使得深度模型更轻量化,可以显著的减少计算花销。但是它只能用于softmax loss function做多分类的模型。还有就是它的模型假设太过于严格。 基准、评估、数据库 作为基准的模型: 常用的模型与压缩的方法 经典的评估方法 假设a是模型M的原始参数个数,a*是已经压缩过模型的参数个数。那么压缩率为 ...
Kd-networks[18]在具有一定大小的kd树上以前馈自底向上的方式计算表示。在kd网络中,在训练和测试时,点云中的输入点数需要相同,这对于很多任务来说并不适用。SSCN[7]利用基于体积网格的卷积,通过只考虑输入点上的CNN输出,具有新颖的速度/内存改进。但是,如果对点云进行稀疏采样,特别是在采样率不均匀的情况下,对于...
At the time of writing, Keras ships with six of these pre-trained modelsalready built into the library: VGG16 VGG19 ResNet50 Inception v3 Xception MobileNet The VGG networks, along with the earlier AlexNet from 2012, follow the now archetypal layout of basic conv nets: a series of convoluti...
deep neural networksinverse problemsIn this work a novel, automated process for determining an appropriate deep neural network architecture and weight initialization based on decision trees is presented. The method maps a collection of decision trees trained on the data into a collection of initialized...
knowledge distillation (KD) Note, this repo is more about pruning (with lottery ticket hypothesis or LTH as a sub-topic), KD, and quantization. For other topics like NAS, see more comprehensive collections (## Related Repos and Websites) at the end of this file. Welcome to send a pull...