Results 71 to 80 of about 98,314 (264)
Local Coupled Extreme Learning Machine Based on Particle Swarm Optimization
Algorithms, 2018 We developed a new method of intelligent optimum strategy for a local coupled extreme learning machine (LC-ELM). In this method, both the weights and biases between the input layer and the hidden layer, as well as the addresses and radiuses in the local ...
Hongli Guo +5 more
doaj +1 more source
Programmable Photonic Extreme Learning Machines
Laser & Photonics ReviewsAbstractPhotonic neural networks offer a promising alternative to traditional electronic systems for machine learning accelerators due to their low latency and energy efficiency. However, the challenge of implementing the backpropagation algorithm during training has limited their development. To address this, alternative machine learning schemes, such
Rausell-Campo, Jose Roberto +3 more
openaire +5 more sources
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
Comparative Analysis of Artificial Neural Networks and Extreme Learning Machine Techniques for Breast Cancer Diagnosis [PDF]
Liaquat National Journal of Cancer CareBackground: Breast cancer is the second dangerous disease that causes death in women. Early detection can reduce mortality rates by 40% or more. The procedures to be carried out in this process create extra labor and financial costs for both the patient
Ulku Veranyurt +3 more
doaj +1 more source
Extreme learning machines [PDF]
, 2019 This thesis introduces novel fast learning algorithms for neural networks namely extreme learning machine (ELM) and its variants.
openaire +2 more sources
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 +8 more
wiley +1 more source
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 +3 more
wiley +1 more source
Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
Advanced Materials, EarlyView.This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen +7 more
wiley +1 more source
Optoelectronic Nanofluidic Neural Networks for Ionic Computing
Advanced Materials, EarlyView.An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang +10 more
wiley +1 more source