Author

An End-to-End Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things

Nakip, M.; Karakayali, K.; Guzelis, C.; Rodoplu, V. (Institute of Electrical and Electronics Engineers Inc., 2021)

We develop a novel end-to-end trainable feature selection-forecasting (FSF) architecture for predictive networks targeted at the Internet of Things (IoT). In contrast with the existing filter-based, wrapper-based and ...

New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration

Aslan, S.N.; Ozalp, R.; Ucar, A.; Guzelis, C. (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) ...

New convolutional neural network models for efficient object recognition with humanoid robots

Aslan, S.N.; Ucar, A.; Guzelis, C. (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 ...

Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection

Nakip, M.; Guzelis, C.; Yildiz, O. (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 ...

Author

An End-to-End Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things ﻿

New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration ﻿

New convolutional neural network models for efficient object recognition with humanoid robots ﻿

Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection ﻿

An End-to-End Trainable Feature Selection-Forecasting Architecture Targeted at the Internet of Things

New CNN and hybrid CNN-LSTM models for learning object manipulation of humanoid robots from demonstration

New convolutional neural network models for efficient object recognition with humanoid robots

Recurrent Trend Predictive Neural Network for Multi-Sensor Fire Detection