Results 21 to 30 of about 98,687 (237)
SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud [PDF]
IEEE International Conference on Robotics and Automation, 2017 We address semantic segmentation of road-objects from 3D LiDAR point clouds. In particular, we wish to detect and categorize instances of interest, such as cars, pedestrians and cyclists.
Bichen Wu +3 more
semanticscholar +1 more source
An Efficient Online Prediction of Host Workloads Using Pruned GRU Neural Nets [PDF]
Social Science Research Network, 2023 Host load prediction is essential for dynamic resource scaling and job scheduling in a cloud computing environment. In this context, workload prediction is challenging because of several issues.
Amin Setayesh +2 more
semanticscholar +1 more source
CAAI Transactions on Intelligence Technology, 2021 A special recurrent neural network (RNN), that is the zeroing neural network (ZNN), is adopted to find solutions to time‐varying quadratic programming (TVQP) problems with equality and inequality constraints.
Xiaoyan Zhang +5 more
doaj +1 more source
Attention‐based novel neural network for mixed frequency data
CAAI Transactions on Intelligence Technology, 2021 It is a common fact that data (features, characteristics or variables) are collected at different sampling frequencies in some fields such as economic and industry.
Xiangpeng Li +3 more
doaj +1 more source
IET Software, 2021 Source code suggestion is the utmost helpful feature in the integrated development environments that helps to quicken software development by suggesting the next possible source code tokens.
Yasir Hussain, Zhiqiu Huang, Yu Zhou
doaj +1 more source
Frontiers in Behavioral Neuroscience, 2022 Mice use ultrasonic vocalizations (USVs) to convey a variety of socially relevant information. These vocalizations are affected by the sex, age, strain, and emotional state of the emitter and can thus be used to characterize it.
Yizhaq Goussha +5 more
semanticscholar +1 more source
Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks [PDF]
Biological Cybernetics, 2012 Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in ...
Bitzer, S., Kiebel, S.
openaire +4 more sources
Deep learning for time series forecasting: The electric load case
CAAI Transactions on Intelligence Technology, 2022 Management and efficient operations in critical infrastructures such as smart grids take huge advantage of accurate power load forecasting, which, due to its non‐linear nature, remains a challenging task.
Alberto Gasparin +2 more
doaj +1 more source
Sensors, 2021 Recording human gestures from a wearable sensor produces valuable information to implement control gestures or in healthcare services. The wearable sensor is required to be small and easily worn.
Edwin Valarezo Añazco +5 more
doaj +1 more source
A hybrid model for fake news detection: Leveraging news content and user comments in fake news
IET Information Security, 2021 Nowadays, social media platforms such as Twitter have become a popular medium for people to spread and consume news because of their easy access and the rapid proliferation of news.
Marwan Albahar
doaj +1 more source