Results 101 to 110 of about 1,532,152 (301)

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Astronomical object recognition by means of neural networks

, 1998
Astronomical wide field imaging deals with Terabytes data sets and requires new strategies for data reduction and analysis. We discuss here the application of different types of neural nets to the detection and extraction of celestial objects ...
Andreon S., Longo G., Tagliaferri R., Zaggia S., Gargiulo G., Capuano N.   +5 more
core   +1 more source

PSANet: Automatic colourisation using position‐spatial attention for natural images

IET Computer Vision
Due to the richness of natural image semantics, natural image colourisation is a challenging problem. Existing methods often suffer from semantic confusion due to insufficient semantic understanding, resulting in unreasonable colour assignments ...
Peng‐Jie Zhu, Yuan‐Yuan Pu, Qiuxia Yang, Siqi Li, Zheng‐Peng Zhao, Hao Wu, Dan Xu   +6 more
doaj   +1 more source

Application of wavelets and artificial neural network for indoor optical wireless communication systems [PDF]

This study investigates the use of error control code, discrete wavelet transform (DWT) and artificial neural network (ANN) to improve the link performance of an indoor optical wireless communication in a physical channel.
Rajbhandari, Sujan
core  

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Process versus Unfolding Semantics for Place/Transition Petri Nets [PDF]

, 1996
In the last few years, the semantics of Petri nets has been investigated in several different ways. Apart from the classical "token game," one can model the behaviour of Petri nets via non-sequential processes, via unfolding constructions, which provide ...
Vladimiro Sassone (16064975), Vladimiro Sassone, Meseguer, José, Sassone, V., Meseguer, J., MONTANARI, UGO GIOVANNI ERASMO, Ugo Montanari, Ugo Montanari (12616129), Sassone V., Meseguer J, Montanari, U., José Meseguer (39091), Montanari, Ugo, Sassone, Vladimiro, José Meseguer   +14 more
core   +2 more sources

GAMNet: Global attention via multi‐scale context for depth estimation algorithm and application

IET Image Processing
Deep neural networks significantly enhance the accuracy of the stereo‐based disparity estimation. Some current methods suffer from inefficient use of the global context information, which will lead to the loss of structural details in ill‐posed areas. To
Huitong Yang, Liang Lei, Haiwei Sang
doaj   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Imaging from temporal data via spiking convolutional neural networks [PDF]

, 2020
A new approach for imaging that is solely based on the time of flight of photons coming from the entire imaged scene, combined with a novel machine learning algorithm for image reconstruction: a spiking convolutional neural network (SCNN) named Spike-SPI
Kapitany, Valentin, Turpin, Alex, Faccio, Daniele, Soraghan, John, Lyons, Ashley, Kirkland, Paul, Di Caterina, Gaetano   +6 more
core   +1 more source

Extrusion Bioprinting for Wound Healing: Innovations in Functionalized Bioinks and Bioprinting Technology

Advanced Materials Technologies, EarlyView.
Extrusion‐based bioprinting (EBB) has emerged as a versatile biofabrication platform capable of precisely depositing bioinks composed of biomaterials, cells, and bioactive agents to generate patient‐specific, biomimetic skin constructs. This paper presents a state‐of‐the‐art and forward‐looking overview of EBB for wound healing, encompassing printing ...
Hien‐Phuong Le, Anh Tuan Trong Tran, Ammara Waheed, Tran Thanh Tung, Dusan Losic   +4 more
wiley   +1 more source