ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices [PDF]
We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs).
Xiangyu Zhang +3 more
semanticscholar +1 more source
Method for predicting cutter remaining life based on multi-scale cyclic convolutional network
In the process of predicting the remaining cutter life, the deep-learning method such as convolutional neural network does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life
Tao Li +5 more
doaj +1 more source
Texture synthesis of ecological plant protection image based on convolution neural network
Texture synthesis technology is an important realistic rendering technology. Texture synthesis technology also has a good application prospect in image rendering and other fields. Convolutional neural network is a very popular technology in recent years.
Libing Hu, Fei Zhou, Xianjun Fu
doaj +1 more source
Forecast Model of TV Show Rating Based on Convolutional Neural Network
The TV show rating analysis and prediction system can collect and transmit information more quickly and quickly upload the information to the database. The convolutional neural network is a multilayer neural network structure that simulates the operating
Lingfeng Wang
doaj +1 more source
PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes [PDF]
Estimating the 6D pose of known objects is important for robots to interact with the real world. The problem is challenging due to the variety of objects as well as the complexity of a scene caused by clutter and occlusions between objects. In this work,
Yu Xiang +3 more
semanticscholar +1 more source
Speech Command Recognition using Artificial Neural Networks
Speech is one of the most effective way for human and machine to interact. This project aims to build Speech Command Recognition System that is capable of predicting the predefined speech commands. Dataset provided by Google’s TensorFlow and AIY teams is
Sushan Poudel, Dr. R Anuradha
doaj +1 more source
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring [PDF]
Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation.
Seungjun Nah +2 more
semanticscholar +1 more source
A Convolutional Neural Network for Modelling Sentences [PDF]
The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture dubbed the Dynamic Convolutional Neural Network (DCNN) that we adopt for the semantic modelling of sentences.
Nal Kalchbrenner +2 more
semanticscholar +1 more source
Compressed CNN Plant Leaf Recognition Model Fused with Bayesian
Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting,in order to reduce the cost of storage and calculation,this paper proposes a plant leaf recognition convolutional ...
YAN Ming, ZHU Liang-kuan, JING Wei-peng
doaj +1 more source
Parallel accelerator design for convolutional neural networks based on FPGA
In recent years, convolutional neural network plays an increasingly important role in many fields. However, power consumption and speed are the main factors limiting its application.
Wang Ting, Chen Binyue, Zhang Fuhai
doaj +1 more source

