Results 101 to 110 of about 185,151 (349)
Ensemble Learning for Visual Recognition
, 2016 Due to the widespread availability of affordable mobile cameras and popularity of social networking, a large variety of visual-based applications are emerging.
Bagheri, Mohammad Ali
core
, 2023 Human activity recognition (HAR) from sensor data has become an attractive research topic due to its application in areas such as healthcare, human-computer interaction and smart environments.
Abdulla, Shahab +3 more
core +1 more source
Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification
Complexity, 2018 The use of ensemble learning, deep learning, and effective document representation methods is currently some of the most common trends to improve the overall accuracy of a text classification/categorization system.
Zeynep H. Kilimci, Selim Akyokus
doaj +1 more source
Interface‐Engineered Binary Framework Composites: Advancing Porous Materials for Precision Medicine
Advanced Materials Interfaces, EarlyView.Binary framework composites integrate two complementary porous architectures into a unified platform, enabling multifunctional design, enhanced structural tunability, and improved physicochemical performance. By combining high surface area, ordered porosity, interfacial synergy, and versatile functionalization, these hybrid materials offer new ...
Navid Rabiee +3 more
wiley +1 more source
IEEE AccessThe COVID-19 pandemic has reshaped education and shifted learning from in-person to online. While this shift offers advantages such as liberating the learning process from time and space constraints and enabling education to occur anywhere and anytime, a
Mayanda Mega Santoni +3 more
doaj +1 more source
Xenes for Sustainable Energy: A Roadmap From First‐Principles Design to Practical Deployment
Advanced Materials Interfaces, EarlyView.Emerging 2D Xenes are advancing from theoretical predictions toward practical energy‐storage and conversion technologies through the integration of first‐principles modelling, experimental synthesis, electrochemical validation, and AI‐assisted materials design, enabling accelerated discovery of high‐performance and sustainable electrochemical systems ...
Onur Karaman, Ceren Karaman
wiley +1 more source
, 2009 In this work, we propose a framework for multimodal data fusion at decision level under a multilayer hierarchical ensemble learning architecture.
Ozay, Mete +2 more
core
Ensemble-Based Deep Reinforcement Learning for Chatbots
, 2019 Trainable chatbots that exhibit fluent and human-like conversations remain a big challenge in artificial intelligence. Deep Reinforcement Learning (DRL) is promising for addressing this challenge, but its successful application remains an open question ...
Hyungtak Choi (17227036) +9 more
core +1 more source
Comparison of Fuzzy Integral-Fuzzy Measure based Ensemble Algorithms with the State-of-the-art Ensemble Algorithms [PDF]
, 2018 The Fuzzy Integral (FI) is a non-linear aggregation operator which enables the fusion of information from multiple sources in respect to a Fuzzy Measure (FM) which captures the worth of both the individual sources and all their possible combinations ...
Agrawal, U. +5 more
core +1 more source
Advanced Materials Technologies, EarlyView.This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding +5 more
wiley +1 more source