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Toplam kayıt 16, listelenen: 1-10
Conditional Weighted Ensemble of Transferred Models for Camera Based Onboard Pedestrian Detection in Railway Driver Support Systems
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)
Pedestrian Detection (PD) is one of the most studied issues of driver assistance systems. Although a tremendous effort is already given to create datasets and to develop classifiers for cars, studies about railway systems ...
Learning Stable Robust Adaptive NARMA Controller for UAV and Its Application to Twin Rotor MIMO Systems
(SPRINGER, 2020)
This study presents a nonlinear auto-regressive moving average (NARMA) based online learning controller algorithm providing adaptability, robustness and the closed loop system stability. Both the controller and the plant ...
Coupling of cell fate selection model enhances DNA damage response and may underlie BE phenomenon
(INST ENGINEERING TECHNOLOGY-IET, 2020)
Double-strand break-induced (DSB) cells send signal that induces DSBs in neighbour cells, resulting in the interaction among cells sharing the same medium. Since p53 network gives oscillatory response to DSBs, such interaction ...
Design of microcontroller-based decentralized controller board to drive chiller systems using PID and fuzzy logic algorithms
(SAGE PUBLICATIONS LTD, 2020)
This study deals with designing a decentralized multi-input multi-output controller board based on a low-cost microcontroller, which drives both parts of variable-speed scroll compressor and electronic-type expansion valve ...
A Multiscale Algorithm for Joint Forecasting-Scheduling to Solve the Massive Access Problem of IoT
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2020)
The massive access problem of the Internet of Things (IoT) is the problem of enabling the wireless access of a massive number of IoT devices to the wired infrastructure. In this article, we describe a multiscale algorithm ...
New convolutional neural network models for efficient object recognition with humanoid robots
(Taylor and Francis Inc., 2021)
Humanoid robots are expected to manipulate the objects they have not previously seen in real-life environments. Hence, it is important that the robots have the object recognition capability. However, object recognition is ...
Learning to move an object by the humanoid robots by using deep reinforcement learning
(IOS Press, 2021)
This paper proposes an algorithm for learning to move the desired object by humanoid robots. In this algorithm, the semantic segmentation algorithm and Deep Reinforcement Learning (DRL) algorithms are combined. The semantic ...
Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection
(Institute of Electrical and Electronics Engineers Inc., 2021)
We propose a Recurrent Trend Predictive Neural Network (rTPNN) for multi-sensor fire detection based on the trend as well as level prediction and fusion of sensor readings. The rTPNN model significantly differs from the ...
New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration
(Springer, 2021)
As the environments that human live are complex and uncontrolled, the object manipulation with humanoid robots is regarded as one of the most challenging tasks. Learning a manipulation skill from human Demonstration (LfD) ...
Design of microcontroller-based decentralized controller board to drive chiller systems using PID and fuzzy logic algorithms
(Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2020)
This study deals with designing a decentralized multi-input multi-output controller board based on a low-cost microcontroller, which drives both parts of variable-speed scroll compressor and electronic-type expansion valve ...