Results 101 to 110 of about 2,019,981 (302)

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

Effect of hyperparameter tuning of machine learning algorithms on the modeling quality of the distribution of three mosquito species in Morocco

Journal of Intelligent Systems
The widespread use of machine learning algorithms in dataset modeling requires a thorough understanding of the various tools likely to improve the modeling quality.
Douider Meriem, Amrani Ibrahim, Abik Mounia   +2 more
doaj   +1 more source

A Statistical Approach to Provide Explainable Convolutional Neural Network Parameter Optimization

International Journal of Computational Intelligence Systems, 2019
Algorithms based on convolutional neural networks (CNNs) have been great attention in image processing due to their ability to find patterns and recognize objects in a wide range of scientific and industrial applications.
Saman Akbarzadeh, Selam Ahderom, Kamal Alameh   +2 more
doaj   +1 more source

Robotic Control for Human–Robot Collaborative Assembly Based on Digital Human Model and Reinforcement Learning

Advanced Robotics Research, EarlyView.
This work presents a robotic control method for human–robot collaborative assembly based on a biomechanics‐constrained digital human model. Reinforcement learning is used to generate physiologically plausible human motion trajectories, which are integrated into a virtual environment for robot control learning.
Bitao Yao, Hongzhou Ai, Wenjun Xu, Zude Zhou, Lihui Wang   +4 more
wiley   +1 more source

Feature-Based Population Initialization for Evolutionary Optimization of Machine Learning Models in Short-Term Solar Power Forecasting

Computation
Nowadays, solar energy is becoming one of the most popular sources of renewable energy worldwide. Traditional fossil fuels cause pollution and climate change, while solar power offers a clean and sustainable alternative.
Aleksei Vakhnin, Harri Niska, Anders V. Lindfors, Mikko Kolehmainen   +3 more
doaj   +1 more source

Bayesian Optimization of Hyperparameters Using Gaussian Processes

, 2019
The goal of this thesis was to implement a practical tool for optimizing hy- perparameters of neural networks using Bayesian optimization. We show the theoretical foundations of Bayesian optimization, including the necessary math- ematical background for
Arnold, Jakub
core  

An Ultra-Fast Power Prediction Method Based on Simplified LSSVM Hyperparameters Optimization for PV Power Smoothing

, 2021
With existing power prediction algorithms, it is difficult to satisfy the requirements for prediction accuracy and time when PV output power fluctuates sharply within seconds, so this paper proposes a high-precision and ultra-fast PV power prediction ...
Zeng Liu, Zishun Peng, Kaijie Chen, Yuxing Dai, Zhenxing Zhao, Ying Chen, Kuiyin Zhao, Huan Wang   +7 more
core   +1 more source

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

Hyperparameters optimization of evolving spiking neural network using artificial bee colony for unsupervised anomaly detection

Journal of Intelligent Systems
Nowadays, anomaly detection in streaming data has gained considerable attention due to the exponential growth in the data gathered by Internet of Things applications. Analyzing and processing vast data volumes requires a system capable of working in real-
Rehan Rabie, Sahran Shahnorbanun, Alyasseri Zaid Abdi Alkareem, Sani Nor Samsiah, Al-Betar Mohammed Azmi   +4 more
doaj   +1 more source

Bayesian Optimization of Hyperparameters in Machine Learning [PDF]

, 2021
Cilj naše diplomske naloge je bil analizirati Bayesovsko optimizacijo na problemu optimizacije hiperparametrov. Podlaga za analizo sta pogosto uporabljani orodji za optimizacijo hiperparametrov: naključno iskanje in iskanje v mreži.
OCEPEK, DAVID
core