Deep neural network–based enhancement for image and video streaming systems: A survey and future directions
Internet-enabled smartphones and ultra-wide displays are transforming a variety of visual
apps spanning from on-demand movies and 360° videos to video-conferencing and live …
apps spanning from on-demand movies and 360° videos to video-conferencing and live …
Machine learning in the air
Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …
learning (ML) is penetrating every facet of our lives, and transforming research in many …
A survey of on-device machine learning: An algorithms and learning theory perspective
The predominant paradigm for using machine learning models on a device is to train a
model in the cloud and perform inference using the trained model on the device. However …
model in the cloud and perform inference using the trained model on the device. However …
Mobisr: Efficient on-device super-resolution through heterogeneous mobile processors
In recent years, convolutional networks have demonstrated unprecedented performance in
the image restoration task of super-resolution (SR). SR entails the upscaling of a single low …
the image restoration task of super-resolution (SR). SR entails the upscaling of a single low …
Countering acoustic adversarial attacks in microphone-equipped smart home devices
Deep neural networks (DNNs) continue to demonstrate superior generalization performance
in an increasing range of applications, including speech recognition and image …
in an increasing range of applications, including speech recognition and image …
Detecting soccer balls with reduced neural networks: a comparison of multiple architectures under constrained hardware scenarios
DDR Meneghetti, TPD Homem, JHR de Oliveira… - Journal of Intelligent & …, 2021 - Springer
Object detection techniques that achieve state-of-the-art detection accuracy employ
convolutional neural networks, implemented to have lower latency in graphics processing …
convolutional neural networks, implemented to have lower latency in graphics processing …
Power-aware FPGA mapping of convolutional neural networks
A Montgomerie-Corcoran, SI Venieris… - … Conference on Field …, 2019 - ieeexplore.ieee.org
With an unprecedented accuracy in numerous AI tasks, convolutional neural networks
(CNNs) are rapidly deployed on power-limited mobile and embedded applications. Existing …
(CNNs) are rapidly deployed on power-limited mobile and embedded applications. Existing …
[PDF][PDF] A survey about intelligent solutions for autonomous vehicles based on FPGA
A Kasem, A Reda, J Vásárhelyi… - Carpathian Journal of …, 2020 - sciendo.com
Safe driving and reducing the number of accidents victims have been the main motivations
for researchers and automotive companies for decades. Today, humanity is very close to …
for researchers and automotive companies for decades. Today, humanity is very close to …
Edge Computing Based Miniature Maps Using Embedded Webserver For Prediction of Malignancy
A Johny, KN Madhusoodanan… - 2022 6th International …, 2022 - ieeexplore.ieee.org
Cancer detection from histopathology images is based on extraction of spatial information
from whole slide images (WSI) using image processing tools. Machine learning algorithms …
from whole slide images (WSI) using image processing tools. Machine learning algorithms …
Detecting Soccer Balls with Reduced Neural Networks
MD De Rizzo, HTP Donadon… - Journal of Intelligent …, 2021 - search.proquest.com
Object detection techniques that achieve state-of-the-art detection accuracy employ
convolutional neural networks, implemented to have lower latency in graphics processing …
convolutional neural networks, implemented to have lower latency in graphics processing …