Results 121 to 130 of about 151,967 (341)

Hyperparameter configurations explored.

, 2018
Hyperparameter configurations explored.
Alf Harbitz (6090902), Vaneeda Allken (636441), Ole Thomas Albert (6090899), Endre Moen (6090896), Ketil Malde (42301), Nils Olav Handegard (516463)   +5 more
core   +1 more source

Wavelength‐Multiplexed 2D Beam Steering via a Passive Diffractive Network

Advanced Optical Materials, EarlyView.
Illustration of a wavelength‐multiplexed diffractive beam steering system, which is composed of K cascaded diffractive layers, each containing phase‐modulating elements that are jointly optimized using deep learning–based optimization. When illuminated with a set of wavelengths {λ1,λ2,…,λNw}$\{ {{{\lambda }_1},{{\lambda }_2},\ldots ,{{\lambda }_{{{N}_w}
Che‐Yung Shen, Yuhang Li, Çağatay Işıl, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan   +5 more
wiley   +1 more source

Enhanced Heart Disease Diagnosis Using Machine Learning Algorithms: A Comparison of Feature Selection

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Heart disease or cardiovascular disease is one of the leading causes of death in the world. Based on WHO data, in 2019, as many as 17.9 million people died from cardiovascular disease.
Hirmayanti, Ema Utami
doaj   +1 more source

Comparative Study of Various Hyperparameter Tuning on Random Forest Classification With SMOTE and Feature Selection Using Genetic Algorithm in Software Defect Prediction

Journal of Electronics Electromedical Engineering and Medical Informatics
Software defect prediction is necessary for desktop and mobile applications. Random Forest defect prediction performance can be significantly increased with the parameter optimization process compared to the default parameter.
Mulia Kevin Suryadi, R. Herteno, Setyo Wahyu Saputro, M. Faisal, Radityo Adi Nugroho   +4 more
semanticscholar   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Strongly Versus Weakly Coupled Data Assimilation in Coupled Systems With Various Inter‐Compartment Interactions

Journal of Advances in Modeling Earth Systems
Coupled data assimilation (CDA) has been attracting researchers' interests to improve Earth system modeling. The CDA methods are classified into two: weakly coupled data assimilation (wCDA), which considers cross‐compartment interaction only in a ...
Norihiro Miwa, Yohei Sawada
doaj   +1 more source

Improved Pacific Decadal Oscillation Prediction by an Optimizing Model Combined Bidirectional Long Short-Term Memory and Multiple Modal Decomposition

Remote Sensing
The Pacific Decadal Oscillation (PDO), as the dominant mode of decadal sea surface temperature variability in the North Pacific, exhibits both interannual and decadal fluctuations that significantly influence global climate.
Hang Yu, Junbo Lei, Pengfei Lin, Tao Zhang, Hailong Liu, Huilin Lai, Lindong Lai, Bowen Zhao, Bo Wu   +8 more
doaj   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Predicting Liquid Natural Gas Consumption via the Multilayer Perceptron Algorithm Using Bayesian Hyperparameter Autotuning

Energies
Reductions in energy consumption and greenhouse gas emissions are required globally. Under this background, the Multilayer Perceptron machine-learning algorithm was used to predict liquid natural gas consumption to improve energy consumption efficiency ...
Hyungah Lee, Woojin Cho, Jong-hyeok Park, Jae-hoi Gu   +3 more
doaj   +1 more source