Recently, the hybrid deep neural network (DNN)-hidden Markov model (HMM) has been shown to significantly improve speech recognition performance over the conventional Gaussian mixture model (GMM)-HMM. The perf
we improve upon prior understanding and performance in complex-valued convolutional neural networks. Using novel derivations of convolutional, down-sampling, non-linear, and affine layers implemented in a complex-valued counterpart to Caffe, we proved results when evaluated against real-valued models in...
Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904–1916 (2015). Article PubMed Google Scholar Girshick, R. Fast r-cnn. In Proceedings of the IEEE International Conference on Computer Vision. 1440–1448 (2015)...
PFCNN: Convolutional Neural Networks on 3D Surfaces Using Parallel Frames Yuqi Yang, Shilin Liu, Hao Pan, Yang Liu, Xin Tong CVPR 2020|June 2020 Download BibTex Surface meshes are widely used shape representations and capture finer geometry data than point clouds or volumetric gr...
Convolutional neural network (CNN) is a deep feed-forward artificial neural network, which is widely used in image recognition. However, this mode highlights the problems that the training time is too long and memory is insufficient. Traditional accelera
et al. Social-stgcnn: A social spatio-temporal graph convolutional neural network for human trajectory prediction. in C. 2020 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 14424–14432 (2020). Sun, J., Jiang, Q. & Lu, C. Recursive social behavior graph for trajectory ...
Deep convolutional neural networks have been proved successful on a wide range of tasks, yet they are still hindered by… arxiv.org As seen in the architecture diagram below, the Saliency-and-Pruning module is embedded in each layer of the convolutional network. The module predicts saliency scor...
Learning Convolutional Neural Networks with Deep Part Embeddings for ICASSP 2019 by Nitin Gupta et al.
Neural networks can be implemented by using purified DNA molecules that interact in a test tube. Convolutional neural networks to classify high-dimensional data have now been realized in vitro, in one of the most complex demonstrations of molecular programming so far. ...
www.nature.com/scientificreports OPEN Point convolutional neural network algorithm for Ising model ground state research based on spring vibration Zhelong Jiang 1,2, Gang Chen 1*, Ruixiu Qiao 1, Pengcheng Feng 1,2, Yihao Chen 1,2, Junjia Su 1,2, Zhiyuan ...