Showing 221 - 240 results of 409 for search '((shine OR ((hinge OR chinges) OR hing)) OR ((spenggl OR (ann OR pingat)) OR ping))', query time: 0.07s Refine Results
  1. 221

    Arabtalk, an implementation for Arabic TTS by Abdulhalim, Yasser Hifny, Qurany, Shady, Hamid, Salah, Rashwan, Muhsen, Atiyya, Muhammad, Ahmed Mahmoud, Ahmed Ragheb, Khallaaf, Galaal

    Published 2011
    “…The system employs Artificial Neural Networks (ANN) statistical prosody based models for duration, energy, and global pitch contour prediction. …”
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    Article
  2. 222

    An efficient technique for human verification using finger stripes geometry by Rahman, Md. Arafatur, Azad, Md. Saiful, Anwar, Farhat

    Published 2007
    “…This finger stripe based verification consists of two main attributes, feature extraction by image processing and feature learning by ANN (Artificial Neural Network). The Distance Based Nearest Neighbor Algorithm, which shows greater accuracy than NN is also applied here. …”
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    Article
  3. 223

    Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

    Published 2013
    “…This article represents the classification of Electromygraphy (EMG) signal for the detection of different predefined hand motions (left, right, up and down) using artificial neural network (ANN). The neural network is of backpropagation type, trained by Levenberg-Marquardt training algorithm. …”
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    Article
  4. 224

    Neural network classifier for hand motion detection from EMG signal by Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

    Published 2011
    “…This paper represents the detection of different predefined hand motions (left, right, up and down) using artificial neural network (ANN). A backpropagation (BP) network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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    Book Chapter
  5. 225

    A novel palmprint segmentation technique by Rotinwa-Akinbile, M. O., Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka

    Published 2011
    “…In this paper, the acquired image undergoes color space conversion and the output is filtered using coefficients obtained from the training of an artificial neural network (ANN) based model coefficient determination technique. …”
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    Proceeding Paper
  6. 226

    Feature extraction of speech signal and heartbeat detection in angry emotion identification by Mohamed, Masnani, Lee, Chee Chuan, Ahmad, Ida Laila

    Published 2013
    “…Then, Artificial Neural Network (ANN) was used to classify each parameter features such as mean fundamental frequency, maximum fundamental frequency, standard deviation fundamental frequency, mean amplitude, pause length ratio and first formant frequency to recognize the emotion. …”
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    Article
  7. 227

    Electricity consumption forecasting using Nonlinear Autoregressive with External (Exogeneous) input neural network by K. G., Tay, Muwafaq, Hassan, Ismail, Shuhaida, Ong, Pauline

    Published 2019
    “…Even though there are previous works of electricity consumption forecasting using Artificial Neural Network (ANN), but most of their data is multivariate data. …”
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    Article
  8. 228
  9. 229

    Signature recognition using artificial neural network by Abushariah, Ahmad A. M., Gunawan, Teddy Surya, Khalifa, Othman Omran, Chebil, Jalel

    Published 2011
    “…For our application, off-line approach will be utilized.Neural Networks (NN) also known as Artificial Neural Networks (ANN) belong to the artificial intelligence approaches, which attempt to mechanize the recognition procedure according to the way a person applies intelligence in visualizing and analyzing[2]. …”
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    Book Chapter
  10. 230

    Multibiometric systems based verification technique by Anwar, Farhat, Rahman, Md. Arafatur, Azad, Md. Saiful

    Published 2009
    “…Artificial Neural Network (ANN) is applied for feature learning and verification process. …”
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    Article
  11. 231

    A new method of vascular point detection using artificial neural network by Kaderi, Mohd Arifin, Aibinu, Abiodun Musa, Salami, Momoh Jimoh Emiyoka

    Published 2012
    “…Performance analysis of the system shows that ANN based technique achieves 100% accuracy on simulated images and minimum of 92% accuracy on RFI obtained from DRIVE database.…”
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    Proceeding Paper
  12. 232

    An evaluation on offline signature verification using artificial neural network approach by Khalifa, Othman Omran, Alam, Md. Khorshed, Hassan Abdalla Hashim, Aisha

    Published 2013
    “…It addresses the offline signature verification technique using Artificial Neural Network (ANN) approach. It also explains the fundamental characteristics of offline signature verification processes and highlights the comparison among various offline signature verification approaches and various signature recognition issues.…”
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    Proceeding Paper
  13. 233

    Optimization of ANPR algorithm on android mobile phone by Mutholib, Abdul, Gunawan, Teddy Surya, Chebil, Jalel, Kartiwi, Mira

    Published 2013
    “…For comparison purpose, the template matching based OCR will be compared to Artificial Neural Network (ANN) based OCR. The optimization on ANPR was performed as currently there is no image processing tool available on the standard Android mobile phone. …”
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    Proceeding Paper
  14. 234

    Load distribution for an intelligent air-cushion track vehicle based on optimal power consumption by Hossain, Altab, Rahman, Mohammed Ataur, Mohiuddin, A. K. M.

    Published 2010
    “…Third, an artificial neural network (ANN) model has been developed which has been trained to predict the total PC for IACTV and to provide illustration how FES might play an important role in the prediction of PC of the vehicle’s intelligent air-cushion system.…”
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    Article
  15. 235

    Power forecasting from solar panels using artificial neural network in UTHM Parit Raja by Mohd Fahmi, Natasha Munirah, Zambri, Nor Aira, Salim, Norhafiz, Sim, Sy Yi

    Published 2021
    “…The collected data are used in developing Artificial Neural Network (ANN) model. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) are the techniques used to forecast the outputs of the PV. …”
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    Article
  16. 236

    Towards realizing the Maqasid Al-Shariah: a critique of Islamic banking and finance practices by Nor Azmi, Hamzah Syahir, Kayadibi, Saim

    Published 2011
    “…The HSBC, University Bank in Ann Arbor and Devon Bank in Chicago offer Islamic banking products in the United States. …”
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    Book Chapter
  17. 237

    Artificial neural network model for predicting wet scrubber performance by Danzomo, Bashir Ahmed, Salami, Momoh Jimoh Eyiomika, Khan, Md. Raisuddin

    Published 2012
    “…The performance fitness of the neural network (MSE = 0.00000107 and R-value = 0.9979) describes the effectiveness of the ANN model in predicting the performance of the scrubber system and the model follows the pattern of the theoretical data describing the scrubber performance at a higher efficiency range.…”
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    Article
  18. 238

    Face recognition from single sample per person by learning of generic discriminant vectors by Hafiz, Fadhlan, Shafie, Amir Akramin, Mohd Mustafah, Yasir

    Published 2012
    “…This paper proposes a development of face recognition based on a combination of traditional eigenface with artificial neural network (ANN), having the face recognition performance boosted by the classification of discriminant vectors learned from a set of generic samples. …”
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    Article
  19. 239

    Self-organizing map approach for determining mobile user location using IEEE 802.11 signals by Mantoro, Teddy, Ayu, Media Anugerah, Nuraini, Asma, Amin, Sulafa Mohd

    Published 2010
    “…SOM as an unsupervised learning techniques of Artificial Neural Network (ANN) capable for summarizing high-dimensional data which cause region of the network to respond similarly to certain input patterns by analyzing the signal strength or signal-to-noise (SNR) of the wireless access points (AP) that enable a wireless networked device to infer the location of wireless client. …”
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    Proceeding Paper
  20. 240