Results 81 to 90 of about 9,482,218 (334)
Advanced Science, EarlyView.Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li +6 more
wiley +1 more source
International Journal of Advanced Robotic SystemsThe model predictive control trajectory planner is a popular and effective robot local motion planner. However, it is challenging to satisfy real-time requirements and implement them on embedded platforms due to their high complexity of solving and ...
Xiaoqing Guan +7 more
doaj +1 more source
Applied Artificial Intelligence, 2020 Outlier detection has received special attention in various fields, mainly for those dealing with machine learning and artificial intelligence. As strong outliers, anomalies are divided into point, contextual and collective outliers.
Rasoul Kiani +2 more
doaj +1 more source
Complexity Analysis of Multilayer Perceptron Neural Network Embedded into a Wireless Sensor Network [PDF]
, 2014 This paper presents computational and message complexity analysis for a multi-layer perceptron neural network, which is implemented in fully distributed and parallel form across a wireless sensor network.
Serpen, Gursel, Gao, Zhenning
core +1 more source
Advanced Science, EarlyView.By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin +12 more
wiley +1 more source
Frontiers in NeuroimagingDiffusion magnetic resonance imaging is sensitive to the microstructural properties of brain tissue. However, estimating clinically and scientifically relevant microstructural properties from the measured signals remains a highly challenging inverse ...
Leevi Kerkelä +4 more
doaj +1 more source
Physics‐Informed Neural Network‐Enabled Forward Prediction and Inverse Design of Ring Origami
Advanced Science, EarlyView.This work presents a KRT‐PINN framework that integrates Kirchhoff rod theory with physics‐informed neural networks for the forward prediction and inverse design of ring origami consisting of closed‐loop rods. The framework predicts stable states of segmented rings with prescribed natural‐curvature profiles and determines the natural‐curvature profiles ...
Luyuan Ning +3 more
wiley +1 more source
Advanced Science, EarlyView.Here, we present an optoelectronic synaptic memtransistor (OSMT) integrating photoresponsive IGZO with contact‐engineered HfO2, enabling electrically and optically tunable synaptic weights. The device demonstrates broad range of tunable conductance states and array‐level image processing, highlighting its potential for intelligent machine vision ...
Donghyun Kang +6 more
wiley +1 more source
Multi-Layer Perceptron Neural Network for an Offline Signature Verification System
, 2021 Signature verification using neural networks is characterized by the use of pre-processing techniques such as normalization, morphological operations and median filtering. In this work, an effective method for offline signature verification system based on multi-layer perceptron (MLP) was proposed.
Nuhu, A.S. +3 more
openaire +2 more sources
A Generative Neuro‐Symbolic AI for Protein Sequence Design
Advanced Science, EarlyView.We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source