Special Section Guest Editorial: Image and Video Compression Using Deep Neural Networks

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Related publications (29)

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Development and Experimental Validation of Dissipative Embedded Column Base Connections for Enhanced Seismic Performance of Steel Moment-Resisting Frames

Dimitrios Lignos, Albano António De Abreu E Presa De Castro E Sousa, Hiroyuki Inamasu

This paper proposes a novel embedded column base (ECB) connection that defies the current paradigm in capacity-designed steel moment-resisting frames (MRFs) where column bases have been traditionally considered as nondissipative. In the proposed concept, a ...

2022

Interface modification to achieve high-efficiency and stable perovskite solar cells

Yuhang Liu, Linfeng Pan, Hongwei Zhu, Zhongjin Shen

The organic-inorganic hybrid perovskite solar cells (PSCs) achieve relatively high power conversion efficiencies (PCEs) over the past few years. However, defects on the surface and at the grain boundaries of the perovskite active layers are critical factor ...

ELSEVIER SCIENCE SA2022

Optimizing Adiabatic Quantum-Flux-Parametron (AQFP) Circuits using an Exact Database

Giovanni De Micheli, Dewmini Sudara Marakkalage

Adiabatic Quantum-Flux-Parametron (AQFP) is a family of superconducting electronic (SCE) circuits exhibiting high energy efficiency. In AQFP technology, logic gates require splitters to drive multiple fanouts and both the logic gates and the splitters are ...

IEEE2021

Deep Polynomial Neural Networks

Grigorios Chrysos

Deep convolutional neural networks (DCNNs) are currently the method of choice both for generative, as well as for discriminative learning in computer vision and machine learning. The success of DCNNs can be attributed to the careful selection of their buil ...

2021

Wavelength-Multiplexed Single-Shot Ptychography

Yves Bellouard

We present multi-wavelength single-shot ptychography, a technique which is ideally suited for imaging dynamically evolving plasmas. Through improvements to single-shot ptychography and a novel probe constraint, wavelength-multiplexed single-shot ptychograp ...

IEEE2020

An Actuation Fault Tolerance Approach to Reconfiguration Planning of Modular Self-folding Robots

Jamie Paik

This paper presents a novel approach to fault tolerant reconfiguration of modular self-folding robots. Among various types of faults that probably occur in the modular system, we focus on the tolerance of complete actuation failure of active modules that m ...

IEEE2020

Convergence Of Variance-Reduced Learning Under Random Reshuffling

Ali H. Sayed, Kun Yuan, Bicheng Ying

Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact minimizers. The existing convergence results assume uniform ...

IEEE2018

Learning Robot Gait Stability using Neural Networks as Sensory Feedback Function for Central Pattern Generators

Auke Ijspeert, José Santos-Victor, Sébastien Gay

In this paper we present a framework to learn a model-free feedback controller for locomotion and balance control of a compliant quadruped robot walking on rough terrain. Having designed an open-loop gait encoded in a Central Pattern Generator (CPG), we us ...

2013

From Discrete Measurements to Bounded Gradient Estimates: A Look at Some Regularizing Structures

Dominique Bonvin, Grégory François, Gene Bunin

Obtaining a reliable gradient estimate for an unknown function when given only its discrete measurements is a common problem in many engineering disciplines. While there are many approaches to obtaining an estimate of a gradient, obtaining lower and upper ...

American Chemical Society2013