Recently, convolutional neural network (CNN)-based data reconstruction has shown especially successful performance when utilized for charged particle tracking with good precision in accelerator and calorimeter
4.11.6 Convolutional neural network Nowadays, the concept of ANN evolved from MLP [156] into advanced deep convolutional neural network [153], are based on an input multiple layer configuration consisting of a hidden structure, and a single output. Convolutional Neural Network (CNN) is a class ...
Convolutional neural network-based deep learning architectures are popular for computer vision tasks like image classification. A convolutional neural network is a type of neural network architecture that takes input images and extracts relevant features to efficiently identify and classify images. CNN uses...
Voice disorders are very common in the global population. Many researchers have conducted research on the identification and classification of voice disorders based on machine learning. As a data-driven algorithm, machine learning requires a large number
深度学习方法:代表方法有R-CNN (Region-based Convolutional Neural Networks)和 YOLO。R-CNN是基于区域的卷积神经网络,结合Region Proposal和CNN,YOLO将图片分为S*S分区,每个分区检测中心点位于该分区的目标。其他方法包括SPP-net、Fast R-CNN、Faster R-CNN、R-FCN、SSD等 ...
Nowthisis why deep learning is calleddeeplearning. Each hidden layer of the convolutional neural network is capable of learning a large number of kernels. The output from this hidden-layer is passed to more layers which are able to learn their own kernels based on theconvolvedimage output from...
[Ranzato07]M.A. Ranzato, C. Poultney, S. Chopra and Y. LeCun, in J. Platt et al., Efficient Learning of Sparse Representations with an Energy-Based Model, Advances in Neural Information Processing Systems (NIPS 2006), MIT Press, 2007. ...
@article{zhang2020ifcnn, title={IFCNN: A general image fusion framework based on convolutional neural network}, author={Zhang, Yu and Liu, Yu and Sun, Peng and Yan, Han and Zhao, Xiaolin and Zhang, Li}, journal={Information Fusion}, volume={54}, pages={99--118}, year={2020}, pub...
CBM Condition-based maintenance CNN Convolution neural network GPIF-CNN Global information fusion-CNN MB-DNN Multibranch deep neural Nnetwork MIF-CNN Multi-information flow CNN SGIF-CNN Simplified global information fusion CNN SM Scheduled maintenance STFT Short-time Fourier transform SVM Support vector ...
Like multi-layer perceptrons andrecurrent neural networks, convolutional neural networks can also be trained using gradient-based optimization techniques. Stochastic, batch, or mini-batch gradient descent algorithms can be used to optimize the parameters of the neural network. Once the CNN has been tra...