Results 181 to 190 of about 123,872 (245)

Ensemble Entropy with Adaptive Deep Fusion for Short-Term Power Load Forecasting. [PDF]

Entropy (Basel)
Wang Y, Niu Y, Li X, Dai X, Wang X, Jiang Y, He C, Zhou L.   +7 more
europepmc   +1 more source

Adaptive Autonomy in Microrobot Motion Control via Deep Reinforcement Learning and Path Planning Synergy

Advanced Intelligent Systems, EarlyView.
This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi, Bairong Zhu, Haoyu Liu, Tingting Yu   +3 more
wiley   +1 more source

A new automatic forecasting method based on explainable deep dendritic artificial neural network. [PDF]

Sci Rep
Bas E, Egrioglu E.
europepmc   +1 more source

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

Advanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

Development and validation of a keypoint region-based convolutional neural network to automate thoracic Cobb angle measurements using whole-spine standing radiographs. [PDF]

Acta Neurochir (Wien)
Dagli MM, Sussman JH, Gujral J, Budihal BR, Kerr M, Yoon JW, Ozturk AK, Cahill PJ, Anari J, Winkelstein BA, Welch WC.   +10 more
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Time series analysis and seasonality trends of SARS-CoV-2 in Ecuador (2020-2024): a four-year study. [PDF]

Front Public Health
Espinosa P, Quirola-Amores P, Lema Asqui S, Terán E.   +3 more
europepmc   +1 more source

SCP‐Pose: Leveraging Structural Consistency Prior Knowledge for Real‐Time Category‐Level 6D Pose Estimation

Advanced Intelligent Systems, EarlyView.
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li, Mingxuan Yu, Xuemei Xie, Zhaozhuo An, Qiyue Li, Xiaodan Song, Guangming Shi   +6 more
wiley   +1 more source

Machine Learning Accelerates Crystallization for Structure Determination

Angewandte Chemie, EarlyView.
Single‐crystal X‐ray diffraction (SCXRD) is often constrained by the difficulty of obtaining suitable crystals. Here, a machine learning‐accelerated co‐crystal discovery workflow is established for a crystalline mate strategy that achieves over 95% prediction accuracy and experimentally delivers 114 co‐crystals from 120 candidates.
Cui‐Zhou Luan, Xue‐Zhi Wang, Jian‐Guo Song, Yu Gu, Jing Wu, Ye‐Ting Wang, Jin‐Feng Liang, Jia‐Le Rao, Mo Xie, Jonathan R. Nitschke, Dan Li   +10 more
wiley   +2 more sources

Predicting Crystal Structures and Ionic Conductivities in Li3YCl6−xBrx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

Advanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source