Results 31 to 40 of about 1,532,491 (274)
Remote Sensing, 2023 High-resolution range profile (HRRP), characterized by its high availability and rich target structural information, has been extensively studied. However, HRRP-based target recognition methods using closed datasets exhibit limitations when it comes to ...
Yingying Kong +3 more
doaj +1 more source
Awesome-META+: Meta-Learning Research and Learning Platform
, 2023 <p> Artificial intelligence technology has already had a profound impact in various fields such as economy, industry, and education, but still limited. Meta-learning, also known as "learning to learn", provides an opportunity for general artificial intelligence, which can break through the current AI bottleneck.
Yuxuan Yang +3 more
openaire +1 more source
When and why does motor preparation arise in recurrent neural network models of motor control?
eLifeDuring delayed ballistic reaches, motor areas consistently display movement-specific activity patterns prior to movement onset. It is unclear why these patterns arise: while they have been proposed to seed an initial neural state from which the movement ...
Marine Schimel +2 more
doaj +1 more source
Online Learning of a Memory for Learning Rates
, 2018 The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks.
Kappler, Daniel +2 more
core +1 more source
Ensembled Deep Learning for the Classification of Human Sperm Head Morphology
Advanced Intelligent Systems, 2022 Infertility is a growing global health concern, with male factor infertility contributing to half of all cases. Semen analysis is crucial to infertility diagnostics.
Lindsay Spencer +4 more
doaj +1 more source
Off-Policy Meta-Reinforcement Learning With Belief-Based Task Inference
IEEE Access, 2022 Meta-reinforcement learning (RL) addresses the problem of sample inefficiency in deep RL by using experience obtained in past tasks for solving a new task.
Takahisa Imagawa +2 more
doaj +1 more source
A New Cloud Robots Training Method Using Cooperative Learning
IEEE Access, 2020 At present, cloud robots tend to be intelligent and cooperative. Based on this, we proposed a teaching method based on Imitation and a learning method that incorporates Incremental Learning and Meta Learning.
Guanglong Du, Zhiyao Wang, Zhelin Li
doaj +1 more source
Air-Conditioning Load Forecasting for Prosumer Based on Meta Ensemble Learning
IEEE Access, 2020 Accurate and reliable prediction of air-conditioning load plays a significant role in prosumer energy management system (EMS), because air-conditioning load accounts for a large proportion of the building's total energy consumption. This paper proposes a
Yaogang Chen, Guoyin Fu, Xuefeng Liu
doaj +1 more source
IEEE Access, 2022 Predicting tip positions of a spring based continuum manipulator is highly challenging due to its nonlinear deformations. External loading on the tip further deteriorates the accuracy.
Alok Ranjan Sahoo, Pavan Chakraborty
doaj +1 more source
Overview of molecular signatures of senescence and associated resources: pros and cons
FEBS Open Bio, EarlyView.Cells can enter a stress response state termed cellular senescence that is involved in various diseases and aging. Detecting these cells is challenging due to the lack of universal biomarkers. This review presents the current state of senescence identification, from biomarkers to molecular signatures, compares tools and approaches, and highlights ...
Orestis A. Ntintas +6 more
wiley +1 more source