• Aucun résultat trouvé

[PDF] Top 20 Deep Learning for Video Modelling

Has 10000 "Deep Learning for Video Modelling" found on our website. Below are the top 20 most common "Deep Learning for Video Modelling".

Deep Learning for Video Modelling

Deep Learning for Video Modelling

... name for the process of computing multiple video descriptors (HOG, HOF and/or MBH) along an optical flow trajectory and aggregating them in their particular ...the deep learning ... Voir le document complet

90

User-Adaptive Editing for 360 degree Video Streaming with Deep Reinforcement Learning

User-Adaptive Editing for 360 degree Video Streaming with Deep Reinforcement Learning

... makes for additional levers to ease streaming and improve Qual- ity of Experience ...(QoE). Deep neural networks have been recently shown to achieve best performance for video streaming ... Voir le document complet

4

Training Compact Deep Learning Models for Video Classification Using Circulant Matrices

Training Compact Deep Learning Models for Video Classification Using Circulant Matrices

... achieve video classification is to perform frame-by-frame image recogni- tion, and to average the results before the classification ...sophisticated video features (features across different frames) using ... Voir le document complet

14

Multimodal and Crossmodal Representation Learning from Textual and Visual Features with Bidirectional Deep Neural Networks for Video Hyperlinking

Multimodal and Crossmodal Representation Learning from Textual and Visual Features with Bidirectional Deep Neural Networks for Video Hyperlinking

... of video hyperlinking is to create hyper- links between different videos and/or video segments based on their ...Each video consists of at least two data streams: a visual stream and an audio ... Voir le document complet

9

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning

... of learning useful representations from video (Mohabi et ...principle for exploiting video for unsupervised learning: pre- diction of future image frames (Softky, 1996; Palm, ... Voir le document complet

19

Hierarchical Multimodal Attention for Deep Video Summarization

Hierarchical Multimodal Attention for Deep Video Summarization

... Summarization. For sports summa- rization the video is not the only source of ...a deep learning algorithm to classify soccer actions from the text timeline provided by several web ...like ... Voir le document complet

9

Deep learning for inter-observer congruency prediction

Deep learning for inter-observer congruency prediction

... prediction, deep features ...either for automatically iden- tifying salient regions in an image or a video, or for studying the impact of different factors on gaze ...(top-down). For ... Voir le document complet

6

Learning to count: A deep learning framework for graphlet count estimation

Learning to count: A deep learning framework for graphlet count estimation

... impressive learning capacity, and efficiency in space compared with traditional kernel or embedding ...developed for regular 1-D, 2-D, 3-D grid data such as text, image or video; while graph is ... Voir le document complet

31

Combining video games and constructionist design to support deep learning in play

Combining video games and constructionist design to support deep learning in play

... using video games in ...“educational video games” have achieved their promise. Similarly, for many years constructionists have engaged children in learning across a variety of contexts, ... Voir le document complet

9

A deep learning approach to Species Distribution Modelling

A deep learning approach to Species Distribution Modelling

... a deep learning approach to the problem in order to improve the predictive ...interest for SDM for more than a decade but our study is the first one bringing empirical evidence that ... Voir le document complet

26

Designing Deep Reinforcement Learning for Human Parameter Exploration

Designing Deep Reinforcement Learning for Human Parameter Exploration

... Co-Explorer. For example, one participant was uncertain in controlling the agent through feedback: “if the agent goes in the right direction, I feel like I should take time to see where it goes”, he ...looking ... Voir le document complet

36

Deep Bilateral Learning for Real-Time Image Enhancement

Deep Bilateral Learning for Real-Time Image Enhancement

... available for the ...machine learning approach where the effect of a reference filter, pipeline, or even subjective manual photo adjustment is learned by a deep net- work that can be evaluated ... Voir le document complet

13

Leveraging video annotations in video-based e-learning

Leveraging video annotations in video-based e-learning

... domains. Video archives ...through video annota- tions, allowing to find specific video ...fers for example access to video through semantic annotations, allowing to look for ... Voir le document complet

8

Deep learning and reinforcement learning methods for grounded goal-oriented dialogue

Deep learning and reinforcement learning methods for grounded goal-oriented dialogue

... images containing three to twenty objects, to avoid trivial or overly complicated images. In total, we keep 77,973 images with 609,543 objects. We verified that this selection does not significantly alter the original ... Voir le document complet

164

An Inertial Newton Algorithm for Deep Learning

An Inertial Newton Algorithm for Deep Learning

... finite-dimensional deep learning optimization models we are aware of yield tame losses J ...Consider for example a DNN with classical activation functions (ReLU, sigmoid, SQNL, tanh, soft plus, soft ... Voir le document complet

7

An Inertial Newton Algorithm for Deep Learning

An Inertial Newton Algorithm for Deep Learning

... – using local geometry of empirical loss functions to obtain steeper descent directions, – using past steps history to design more larger step sizes in the present. The first approach is akin to quasi-Newton methods ... Voir le document complet

30

Deep learning for 3D hand biometric systems

Deep learning for 3D hand biometric systems

... putational complexity yielded by the cost of computing the forward and inverse graph Fourier transform. Furthermore, such architectures have O (n) parameters per layer, and no guarantee of spatial localization of the ... Voir le document complet

162

Deep learning for discovering new product opportunities

Deep learning for discovering new product opportunities

... Given a customer feature vector inference on card attribute preferences is performed as a forward pass of the Deep Neural Network model. high income high credit score:[r] ... Voir le document complet

67

Deep learning on attributed graphs

Deep learning on attributed graphs

... ) for reasoning tasks and Brockschmidt et al. ( 2018 ) for code ...ligands for a specific binding site on a protein (analogous to finding a key for a keyhole) could been seen as graph ... Voir le document complet

128

A review on deep reinforcement learning for fluid mechanics

A review on deep reinforcement learning for fluid mechanics

... BSTRACT Deep reinforcement learning (DRL) has recently been adopted in a wide range of physics and engineering domains for its ability to solve decision- making problems that were previously out of ... Voir le document complet

24

Show all 10000 documents...