Distributed deep neural networks over the cloud, the edge and end devices
S Teerapittayanon, B McDanel… - 2017 IEEE 37th …, 2017 - ieeexplore.ieee.org
We propose distributed deep neural networks (DDNNs) over distributed computing
hierarchies, consisting of the cloud, the edge (fog) and end devices. While being able to …
hierarchies, consisting of the cloud, the edge (fog) and end devices. While being able to …
Deep coupled ISTA network for multi-modal image super-resolution
X Deng, PL Dragotti - IEEE Transactions on Image Processing, 2019 - ieeexplore.ieee.org
Given a low-resolution (LR) image, multi-modal image super-resolution (MISR) aims to find
the high-resolution (HR) version of this image with the guidance of an HR image from …
the high-resolution (HR) version of this image with the guidance of an HR image from …
Bidirectional joint representation learning with symmetrical deep neural networks for multimodal and crossmodal applications
Common approaches to problems involving multiple modalities (classification, retrieval,
hyperlinking, etc.) are early fusion of the initial modalities and crossmodal translation from …
hyperlinking, etc.) are early fusion of the initial modalities and crossmodal translation from …
Joint embeddings with multimodal cues for video-text retrieval
For multimedia applications, constructing a joint representation that could carry information
for multiple modalities could be very conducive for downstream use cases. In this paper, we …
for multiple modalities could be very conducive for downstream use cases. In this paper, we …
Multimodal and crossmodal representation learning from textual and visual features with bidirectional deep neural networks for video hyperlinking
Video hyperlinking represents a classical example of multimodal problems. Common
approaches to such problems are early fusion of the initial modalities and crossmodal …
approaches to such problems are early fusion of the initial modalities and crossmodal …
Deep sparse coding for invariant multimodal halle berry neurons
Deep feed-forward convolutional neural networks (CNNs) have become ubiquitous in
virtually all machine learning and computer vision challenges; however, advancements in …
virtually all machine learning and computer vision challenges; however, advancements in …
Neighbourhood structure preserving cross-modal embedding for video hyperlinking
Video hyperlinking is a task aiming to enhance the accessibility of large archives, by
establishing links between fragments of videos. The links model the aboutness between …
establishing links between fragments of videos. The links model the aboutness between …
Plan optimization for creating bilingual dictionaries of low-resource languages
AH Nasution, Y Murakami… - … Conference on Culture …, 2017 - ieeexplore.ieee.org
The constraint-based approach has been proven useful for inducing bilingual lexicons for
closely-related low-resource languages. When we want to create multiple bilingual …
closely-related low-resource languages. When we want to create multiple bilingual …
Image denoising neural network architecture and method of training the same
M El-Khamy, I Fedorov, J Lee - US Patent 10,726,525, 2020 - Google Patents
US10726525B2 - Image denoising neural network architecture and method of training the same
- Google Patents US10726525B2 - Image denoising neural network architecture and method …
- Google Patents US10726525B2 - Image denoising neural network architecture and method …
Generative adversarial networks for multimodal representation learning in video hyperlinking
Continuous multimodal representations suitable for multimodal information retrieval are
usually obtained with methods that heavily rely on multimodal autoencoders. In video …
usually obtained with methods that heavily rely on multimodal autoencoders. In video …