Results 101 to 110 of about 545,363 (263)

Ensemble Learning with Local Diversity

, 2006
The concept of Diversity is now recognized as a key characteristic of successful ensembles of predictors. In this paper we investigate an algorithm to generate diversity locally in regression ensembles of neural networks, which is based on the idea of imposing a neighborhood relation over the set of learners.
Ricardo Ñanculef, Carlos Valle, Héctor Allende, Claudio Moraga   +3 more
openaire   +3 more sources

Decoding Naturalistic Episodic Memory with Artificial Intelligence and Brain‐Machine Interface

Advanced Science, EarlyView.
Episodic memory weaves together what, where, and when of experience into a personal narrative. Cutting‐edge AI models may decode this intricate process in real‐life settings, revealing how neural activity encodes naturalistic memories. By merging AI with brain–machine interfaces, researchers are edging closer to mapping and even engineering memory ...
Dong Song
wiley   +1 more source

Learnable Diffusion Framework for Mouse V1 Neural Decoding

Advanced Science, EarlyView.
We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng, Peter S. Schwendeman, Yuanfang Guan   +2 more
wiley   +1 more source

An adaptive ensemble feature selection technique for model-agnostic diabetes prediction

Scientific Reports
Ensemble learning aggregates several models’ outputs to improve the overall model’s performance. Ensemble feature selection separating the appropriate features from the extra and non-essential features. In this paper, the main focus will be to expand the
K. Natarajan, Dhanalakshmi Baskaran, Selvakumar Kamalanathan   +2 more
doaj   +1 more source

Ensembling Supervised and Unsupervised Machine Learning Algorithms for Detecting Distributed Denial of Service Attacks

Algorithms
The distributed denial of service (DDoS) attack is one of the most pernicious threats in cyberspace. Catastrophic failures over the past two decades have resulted in catastrophic and costly disruption of services across all sectors and critical ...
Saikat Das, Mohammad Ashrafuzzaman, Frederick T. Sheldon, Sajjan Shiva   +3 more
doaj   +1 more source

Optimal weighted parameters of ensemble convolutional neural networks based on a differential evolution algorithm for enhancing pornographic image classification

Engineering and Applied Science Research, 2021
Use of ensemble convolutional neural networks (CNNs) has become a more robust strategy to improve image classification performance. However, the success of the ensemble method depends on appropriately selecting the optimal weighted parameters. This paper
Sarayut Gonwirat, Olarik Surinta
doaj  

Nanoscale Spatial Organization of ARC High‐ and Low‐Order Assemblies at Excitatory Synapses

Advanced Science, EarlyView.
ARC (Activity‐Regulated Cytoskeleton‐Associated protein) mediates synaptic plasticity by forming nanoscale assemblies in neurons. Using super‐resolution microscopy and time‐resolved anisotropy with targeted tagging, the study reveals low‐order ARC assemblies at synapses colocalizing with AMPARs, semi‐circular structures at endocytic zones, and 60–80 nm
Martina Damenti, Giovanna Coceano, Mariline Mendes Silva, Jonatan Alvelid, Chiara Sgattoni, Andrea Volpato, Lea Rems, Luciano A. Masullo, Eduard M. Unterauer, Rafal Kowalewski, Lucie Delemotte, Erdinc Sezgin, Ralf Jungmann, Ilaria Testa   +13 more
wiley   +1 more source

Ensemble learning for predicting subsurface bearing layer depths in Tokyo

Results in Engineering
In order to improve the accuracy of geotechnical investigations, this study developed an ensemble learning method for predicting the depth of the bearing layer in Tokyo. Due to the limitations of traditional geotechnical surveys and the need for detailed
Yuxin Cong, Shinya Inazumi
doaj   +1 more source

SpatialESD: Spatial Ensemble Domain Detection in Spatial Transcriptomics

Advanced Science, EarlyView.
ABSTRACT Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial
Hongyan Cao, Gaiqin Liu, Jingyi Xia, Runle Chen, Tong Wang, Xiaoling Yang, Ruiling Fang, Yanhong Luo, Ping Zeng, Hongmei Yu, Yanbo Zhang, Yuehua Cui   +11 more
wiley   +1 more source

Machine‐Learning Microfluidic Minute‐Scale Microorganism Metrics Monitoring(M6)

Advanced Science, EarlyView.
ABSTRACT On‐site monitoring of microorganisms remains challenging because of low concentrations, strong background interference, and dynamic aerosol diffusion, particularly for aerosol‐transmitted pathogens. Here, we report a rapid detection platform that integrates a Puri‐focusing microfluidic chip, electrochemical impedance spectroscopy (EIS), and ...
Ning Yang, Jiahao Ding, Si Chen, Lijie Yan, Shichao Ding, Lavonda Li, Junyi Sun, Haodong Liu, Tongge Li, Ning Liu, Mingji Wei, Xiaoyong Zhu, Xiaobo Zou, Shouqi Yuan, Xingcai Zhang   +14 more
wiley   +1 more source