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Full-Text Articles in Engineering
Gender Classification: A Convolutional Neural Network Approach, Shan Sung Liew, Mohamed Khalil Hani, Syafeeza Ahmad Radzi, Rabia Bakhteri
Gender Classification: A Convolutional Neural Network Approach, Shan Sung Liew, Mohamed Khalil Hani, Syafeeza Ahmad Radzi, Rabia Bakhteri
Turkish Journal of Electrical Engineering and Computer Sciences
An approach using a convolutional neural network (CNN) is proposed for real-time gender classification based on facial images. The proposed CNN architecture exhibits a much reduced design complexity when compared with other CNN solutions applied in pattern recognition. The number of processing layers in the CNN is reduced to only four by fusing the convolutional and subsampling layers. Unlike in conventional CNNs, we replace the convolution operation with cross-correlation, hence reducing the computational load. The network is trained using a second-order backpropagation learning algorithm with annealed global learning rates. Performance evaluation of the proposed CNN solution is conducted on two …
Recognition System Of Indonesia Sign Language Based On Sensor And Artificial Neural Network, Endang Supriyati, Mohammad Iqbal
Recognition System Of Indonesia Sign Language Based On Sensor And Artificial Neural Network, Endang Supriyati, Mohammad Iqbal
Makara Journal of Technology
Sign language as a kind of gestures is one of the most natural ways of communication for most people in deaf community. The aim of the sign language recognition is to provide a translation for sign gestures into meaningful text or speech so that communication between deaf and hearing society can easily be made. In this research, the Indonesian sign language recognition system based on flex sensors and an accelerometer is developed. This recognition system uses a sensory glove to capture data. The sensor data that are processed into feature vector are the 5-fingers bending and the palm acceleration when …
Controlling The Chaotic Discrete-Hénon System Using A Feedforward Neural Network With An Adaptive Learning Rate, Kürşad Gökce, Yilmaz Uyaroğlu
Controlling The Chaotic Discrete-Hénon System Using A Feedforward Neural Network With An Adaptive Learning Rate, Kürşad Gökce, Yilmaz Uyaroğlu
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.
Control Chart Pattern Recognition Using Artificial Neural Networks, Şeref Sağiroğlu, Erkan Beşdok, Mehmet Erler
Control Chart Pattern Recognition Using Artificial Neural Networks, Şeref Sağiroğlu, Erkan Beşdok, Mehmet Erler
Turkish Journal of Electrical Engineering and Computer Sciences
Precise and fast control chart pattern (CCP) recognition is important for monitoring process environments to achieve appropriate control and to produce high quality products. CCPs can exhibit six types of pattern: normal, cyclic, increasing trend, decreasing trend, upward shift and downward shift. Except for normal patterns, all other patterns indicate that the process being monitored is not functioning correctly and requires adjustment. This paper describes a new type of neural network for speeding up the training process and to compare three training algorithms in terms of speed, performance and parameter complexity for CCP recognition. The networks are multilayered perceptrons trained …