Results 121 to 130 of about 9,482,218 (334)
This report examines the fault tolerance of multi-layer perceptron networks. First, the operation of a single perceptron unit is analysed, and it is found that they are highly fault tolerant. This suggests that neural networks composed from these units
George Bolt, Perceptron Networks George
core
NICE: A Two‐Step Non‐Invasive Framework for Embryo cfDNA Read Enrichment and Quality Assessment
The non‐invasive NICE framework, built on an ensemble stacking machine learning model, prioritizes embryos by analyzing cell‐free DNA from spent culture medium. By integrating multimodal signals, including genomic and epigenetic profiles, this automated approach standardizes morphological assessment without human bias, paving the way for more precise ...
Xueya Zhou +6 more
wiley +1 more source
We propose a designing of multi-layer neural networks using 2D NAND flash memory cell as a high-density and reliable synaptic device. Our operation scheme eliminates the waste of NAND flash cells and allows analogue input values.
Sung-Tae Lee +6 more
doaj +1 more source
Seismic Signal Classification using Multi-Layer Perceptron Neural Network
aim of the present study is to investigate and explore the capability of the multilayer perceptron neural network to classify seismic signals recorded by the local seismic network of Agadir (M orocco). The problem is divided into two main steps, the feature extraction step and classification step .
Abderrahman Atmani +3 more
openaire +1 more source
Análise das redes neurais complexas na detecção de espículas e piscadas em sinais de EEG [PDF]
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Elétrica.Essa dissertação tem o objetivo de analisar a capacidade da rede CMLP de separar as espículas das piscadas em sinais de ...
Travessa, Sheila Santisi
core
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu +8 more
wiley +1 more source
Physics-informed neural networks have gained wide application due to their data efficiency and generation ability. Nevertheless, their application is restricted in practical engineering problems where complex physical mechanisms make it difficult to ...
Zepeng Han +4 more
doaj +1 more source
ARTIFICIAL NEURAL NETWORK MULTI-LAYER PERCEPTRON FOR DIAGNOSIS OF DIABETES MELLITUS
Diabetes Mellitus is a disease caused by an unhealthy lifestyle, so blood sugar is not controlled, causing complications. This disease is one of the most dangerous diseases in the world. Approximately 422 million people worldwide have diabetes, the majority living in low- and middle-income countries, and 1.5 million deaths are caused by diabetes each ...
Ofelia Cizela da Costa Tavares +1 more
openaire +1 more source
A feed forward neural network approach for matrix computations [PDF]
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A new neural network approach for performing matrix computations is presented. The idea of this approach is to construct a feed-forward neural network (FNN)
Al-Mudhaf, Ali F
core +3 more sources
KFO‐Atlas reveals how real‐world aromas are organized as structured mixtures rather than individual molecules. Building on these principles, KFO‐Gen, a generative AI framework, designs perceptually valid aroma formulations and reconstructs meat‐like aromas exclusively from plant‐derived odorants, providing a foundation for mixture‐level studies and AI ...
Jingzhi Zhang +5 more
wiley +1 more source

