Browsing by Keywords "Artificial neural networks"
Now showing items 1-16 of 16
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Activity recognition invariant to sensor orientation with wearable motion sensors
(MDPI AG, 2017)Most activity recognition studies that employ wearable sensors assume that the sensors are attached at pre-determined positions and orientations that do not change over time. Since this is not the case in practice, it is ... -
An approach based on sound classification to predict soundscape perception through machine learning
(Bilkent University, 2021-06)A growing amount of literature and a series of ISO standards focus on concept, data collection, and data analysis methods of soundscapes. Yet, this field of research still lacks predictive models. We hypothesize that machine ... -
Classifying human leg motions with uniaxial piezoelectric gyroscopes
(2009)This paper provides a comparative study on the different techniques of classifying human leg motions that are performed using two low-cost uniaxial piezoelectric gyroscopes worn on the leg. A number of feature sets, extracted ... -
Comparative analysis of different approaches to target classification and localization with sonar
(IEEE, 2001-08)The comparison of different classification and fusion techniques was done for target classification and localization with sonar. Target localization performance of artificial neural networks (ANN) was found to be better ... -
A comparative analysis of different approaches to target differentiation and localization using infrared sensors
(Bilkent University, 2006)This study compares the performances of various techniques for the differentiation and localization of commonly encountered features in indoor environments, such as planes, corners, edges, and cylinders, possibly with ... -
Comparative analysis of different approaches to target differentiation and localization with sonar
(Elsevier, 2003)This study compares the performances of different methods for the differentiation and localization of commonly encountered features in indoor environments. Differentiation of such features is of interest for intelligent ... -
Comparative study on classifying human activities with miniature inertial and magnetic sensors
(Elsevier, 2010)This paper provides a comparative study on the different techniques of classifying human activities that are performed using body-worn miniature inertial and magnetic sensors. The classification techniques implemented and ... -
Farklı yapay sinir ağı temelli sınıflandırıcılar ile insan hareketi tanımlama
(IEEE, 2017-05)İnsan Hareketi Tanımlanması, taşıdığı önem ve sınırlı öznitelik vektörü ile yüksek sınıflandırma oranlarına ulaşmasında karşılaşılan zorluk nedeniyle popüler bir araştırma konusudur. Bireylerin hareket ölçülebilirliginin ... -
Leg motion classification with artificial neural networks using wavelet-based features of gyroscope signals
(2011)We extract the informative features of gyroscope signals using the discrete wavelet transform (DWT) decomposition and provide them as input to multi-layer feed-forward artificial neural networks (ANNs) for leg motion ... -
Neural network-based target differentiation using sonar for robotics applications
(IEEE, 2000-08)This study investigates the processing of sonar signals using neural networks for robust differentiation of commonly encountered features in indoor robot environments. The neural network can differentiate more targets with ... -
Neural networks for improved target differentiation and localization with sonar
(Pergamon Press, 2001)This study investigates the processing of sonar signals using neural networks for robust differentiation of commonly encountered features in indoor robot environments. Differentiation of such features is of interest for ... -
Prediction of cryptocurrency returns using machine learning
(Springer, 2020-04)In this study, the predictability of the most liquid twelve cryptocurrencies are analyzed at the daily and minute level frequencies using the machine learning classification algorithms including the support vector machines, ... -
Recognizing targets from infrared intensity scan patterns using artificial neural networks
(S P I E - International Society for Optical Engineering, 2009-01-30)This study investigates the use of simple, low-cost infrared sensors for the recognition of geometry and surface type of commonly encountered features or targets in indoor environments, such as planes, corners, and edges. ... -
Transform pre-processing for neural networks for object recognition and localization with sonar
(SPIE, 2003)We investigate the pre-processing of sonar signals prior to using neural networks for robust differentiation of commonly encountered features in indoor environments. Amplitude and time-of-flight measurement patterns acquired ... -
Yapay sinir ağlarında yeni bir ön değer atama yöntemi: laplasyen
(IEEE, 2018-05)Makine öğrenimi alanında yapay sinir ağlarının popülerliği 2006 yılında derin öğrenme kavramının yerleşmesi sonrasında günden güne artmaktadır. Derin sinir ağlarının eğitiminde başarı yüzdelerini önemli oranda etkileyen ... -
Yeni bir ögrenme algoritması: SinAdaMax
(IEEE, 2019-04)Yapay Sinir Ağları yaklaşık 21. yüzyılın ilk 10 yılından sonra başlayan ‘Derin Ögrenme’ çağından beri makine öğrenmesi alanını büyük ölçüde etkilemektedir. Sinir ağı eğitimi başarısı ağ parametrelerini modifiye eden ...
