Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Methods for image denoising using convolutional neural network: a review
AE Ilesanmi, TO Ilesanmi - Complex & Intelligent Systems, 2021 - Springer
Image denoising faces significant challenges, arising from the sources of noise. Specifically,
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
Gaussian, impulse, salt, pepper, and speckle noise are complicated sources of noise in …
An edge intelligence empowered flooding process prediction using Internet of things in smart city
Floods result in substantial damage throughout the world every year. Accurate predictions of
floods can significantly alleviate casualties and property losses. However, due to the …
floods can significantly alleviate casualties and property losses. However, due to the …
Traffic flow prediction based on deep learning in internet of vehicles
In Internet of Vehicles (IoV), accurate traffic flow prediction is helpful for analyzing road
condition and then timely feedback traffic information to managers as well as travelers …
condition and then timely feedback traffic information to managers as well as travelers …
Feature normalized knowledge distillation for image classification
K Xu, L Rui, Y Li, L Gu - European conference on computer vision, 2020 - Springer
Abstract Knowledge Distillation (KD) transfers the knowledge from a cumbersome teacher
model to a lightweight student network. Since a single image may reasonably relate to …
model to a lightweight student network. Since a single image may reasonably relate to …
An intelligent caching strategy considering time-space characteristics in vehicular named data networks
In the Internet of Vehicles (IoV), the classic TCP/IP still plays an important role for data
transmission, traffic control and address assignment. However, with increasing requirements …
transmission, traffic control and address assignment. However, with increasing requirements …
[LIBRO][B] Introduction to infrared and electro-optical systems
RG Driggers, MH Friedman, JW Devitt, O Furxhi… - 2022 - books.google.com
This newly revised and updated edition offers a current and complete introduction to the
analysis and design of Electro-Optical (EO) imaging systems. The Third Edition provides …
analysis and design of Electro-Optical (EO) imaging systems. The Third Edition provides …
Convolutional Neural Networks for forecasting flood process in Internet-of-Things enabled smart city
With the advancement of water conservancy informatization based on Internet of Things
(IoT), the hydrological data are increasingly enriched. As a result, more and more algorithms …
(IoT), the hydrological data are increasingly enriched. As a result, more and more algorithms …
Memory-efficient deformable convolution based joint denoising and demosaicing for UHD images
This paper introduces deformable convolution in deep learning based joint denoising and
demosaicing (JDD), which yields more adaptable representation and larger receptive fields …
demosaicing (JDD), which yields more adaptable representation and larger receptive fields …
An intelligent path planning scheme of autonomous vehicles platoon using deep reinforcement learning on network edge
Recent advancements in Intelligent Transportation Systems suggest that the roads will
gradually be filled with autonomous vehicles that are able to drive themselves while …
gradually be filled with autonomous vehicles that are able to drive themselves while …