Results 51 to 60 of about 21,150,821 (215)
Handling negative mentions on social media channels using deep learning
Journal of Information and Telecommunication, 2019 Social media channels such as social networks, forum or online blogs have been emerging as major sources from which brands can gather user opinions about their products, especially the negative mentions.
Khuong Vo +6 more
doaj +1 more source
Mask RCNN-based Single Shot Multibox Detector For Gesture Recognition In Physical Education
Journal of Applied Science and Engineering, 2022 Human-computer interaction (HCI) is an important supporting technology in the computer vision area, especially in physical education. HCI can promote the efficiency of physical education class, which is of great help to improve the learning efficiency ...
Tao Feng
doaj +1 more source
Applied Sciences, 2023 A memory-type control chart is an important tool of statistical process control for monitoring small to moderate shifts in the manufacturing process. Using the prior information by the Bayesian approach is helpful in control charts.
Imad Khan +5 more
doaj +1 more source
Exploring the Encoding Layer and Loss Function in End-to-End Speaker and Language Recognition System [PDF]
The Speaker and Language Recognition Workshop, 2018 In this paper, we explore the encoding/pooling layer and loss function in the end-to-end speaker and language recognition system. First, a unified and interpretable end-to-end system for both speaker and language recognition is developed.
Weicheng Cai, Jinkun Chen, Ming Li
semanticscholar +1 more source
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Training deep neural networks is inherently subject to the predefined and fixed loss functions during optimizing. To improve learning efficiency, we develop Stochastic Loss Function (SLF) to dynamically and automatically generating appropriate gradients to train deep networks in the same round of back-propagation, while maintaining the completeness and
Qingliang Liu, Jinmei Lai
openaire +2 more sources
A Context-Aware Loss Function for Action Spotting in Soccer Videos [PDF]
Computer Vision and Pattern Recognition, 2019 In video understanding, action spotting consists in temporally localizing human-induced events annotated with single timestamps. In this paper, we propose a novel loss function that specifically considers the temporal context naturally present around ...
A. Cioppa +6 more
semanticscholar +1 more source
Competitive on-line learning with a convex loss function [PDF]
, 2005 We consider the problem of sequential decision making under uncertainty in which the loss caused by a decision depends on the following binary observation. In competitive on-line learning, the goal is to design decision algorithms that are almost as good
Vovk, Vladimir
core +3 more sources
Robust Loss Functions under Label Noise for Deep Neural Networks
, 2017 In many applications of classifier learning, training data suffers from label noise. Deep networks are learned using huge training data where the problem of noisy labels is particularly relevant. The current techniques proposed for learning deep networks
Ghosh, Aritra +2 more
core +1 more source
The Population of Dark Matter Subhaloes: Mass Functions and Average Mass Loss Rates
, 2007 Using a cosmological N-Body simulation and a sample of re-simulated cluster-like haloes, we study the mass loss rates of dark matter subhaloes, and interpret the mass function of subhaloes at redshift zero in terms of the evolution of the mass function ...
Carlo Giocoli +8 more
core +1 more source
Italian National Conference on Sensors, 2020 Deep learning has been employed to prognostic and health management of automotive and aerospace with promising results. Literature in this area has revealed that most contributions regarding deep learning is largely focused on the model’s architecture ...
D. Rengasamy +4 more
semanticscholar +1 more source