Results 111 to 120 of about 9,482,218 (334)

Biochemically Constrained Multi‐Omics Integration Reveals Protein–Metabolite Dependencies Across Diseases

Advanced Science, EarlyView.
ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao, Na Zhou, Ruotong Liu, Xiaofei Li, Jian Li, Fuzhong Xue, Qingzhen Hou   +6 more
wiley   +1 more source

Multilayer Perceptron Neural Networks Model for Meteosat Second Generation SEVIRI Daytime Cloud Masking

Remote Sensing, 2015
A multilayer perceptron neural network cloud mask for Meteosat Second Generation SEVIRI (Spinning Enhanced Visible and Infrared Imager) images is introduced and evaluated. The model is trained for cloud detection on MSG SEVIRI daytime data.
Alireza Taravat, Simon Proud, Simone Peronaci, Fabio Del Frate, Natascha Oppelt   +4 more
doaj   +1 more source

A Current Mode CMOS Multi Layer Perceptron Chip

, 1996
An analog VLSI neural network integrated circuit is presented. It consist of a feedforward multi layer perceptron (MLP) network with 64 inputs, 64 hidden neurons and 10 outputs.
CAVIGLIA, DANIELE, G. M. BO, VALLE, MAURIZIO   +2 more
core   +1 more source

Machine Learning‐Driven Design of Multicomponent Bone Inorganic Matrix Mimicking Scaffolds for Osteogenesis Enhanced by Neurogenesis

Advanced Science, EarlyView.
Schematic illustration of development of experimental datasets and algorithm models, screening and preparation of the scaffolds and their applications in vivo. ABSTRACT Bone defects require materials with osteogenic, neurogenic, and angiogenic activity, yet designing such materials within high‐dimensional compositional spaces remains challenging. Here,
Kunlu Lin, Ying Yang, Chuyao Zhou, Hanyue Mao, Zhiquan Zhang, Libangxi Liu, Xiaoying Yu, Haoming Liu, Long Liu, Xiaoyan Wang   +9 more
wiley   +1 more source

Progressive Multi-stage Image Denoising Algorithm Combining Convolutional Neural Network andMulti-layer Perceptron [PDF]

Jisuanji kexue
Among the existing image denoising methods based on deep learning,there are problems at the network architecture dimension that single-stage network is hard to represents feature dependency and it is difficult to reconstruct clear images in complex ...
XUE Jinqiang, WU Qin
doaj   +1 more source

Insurability Challenges Under Uncertainty: An Attempt to Use the Artificial Neural Network for the Prediction of Losses from Natural Disasters [PDF]

The main difficulty for natural disaster insurance derives from the uncertainty of an event’s damages. Insurers cannot precisely appreciate the weight of natural hazards because of risk dependences.
Nouri Chtourou, Rochdi Feki, Rim Jemli
core  

Spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification

, 2022
This paper proposes a novel spectral-spatial multi-layer perceptron network for hyperspectral image land cover classification. Current deep learning-based methods have limitations in spectral and spatial feature representation of hyperspectral images ...
Xiong Tan, Zhixiang Xue
core   +1 more source

Application of artificial neural networks for hydrological modelling in Karst

Građevinar, 2018
The possibility of short-term water flow forecasting in a karst region is presented in this paper. Four state-of-the-art machine learning algorithms are used for the one day ahead forecasting: multi-layer perceptron neural network, radial basis function ...
Miljan Kovačević, Nenad Ivanišević, Tina Dašić, Ljubo Marković   +3 more
doaj   +1 more source

A Bioinspired, Multimodal Soft Tactile Skin with Task‐Adaptive Perception for Intelligent Robotic Manipulation

Advanced Science, EarlyView.
Perception in robotic manipulation improves through the cooperative and complementary operation of biologically inspired multimodal tactile sensors. Receptor‐specific contribution analysis identifies which sensing modalities are required for specific tactile tasks.
Yu‐Jin Lee, Hyeonung Kang, Ju Yeon Woo, Daekyum Kim, Chang‐Soo Han   +4 more
wiley   +1 more source

Floating-Point Quantization Analysis of Multi-Layer Perceptron Artificial Neural Networks

Journal of Signal Processing Systems
AbstractThe impact of quantization in Multi-Layer Perceptron (MLP) Artificial Neural Networks (ANNs) is presented in this paper. In this architecture, the constant increase in size and the demand to decrease bit precision are two factors that contribute to the significant enlargement of quantization errors.
Hussein M. H. Al-Rikabi, Balázs Renczes
openaire   +1 more source