[PDF] Top 20 A deep learning method for pathological voice detection using convolutional deep belief networks

... detecting pathological voice disorders such as vocal cord paralysis or Reinke’s edema is a challenging and important medical classification ...While deep learning techniques have achieved ... See full document

... automatic pathological voice detection ...Saarbruecken Voice Database, and achieved 67% classification accuracy with neutral sustained vowel ...machine learning algorithms, deep ... See full document

... of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object clas- sification, achieving ... See full document

... with using the common sample patch selection methods (such as the random, central, and moment bounding (MB) box methods) for our specific purpose of slope failure detection ...object detection [37]. ... See full document

... Social Networks (OSNs), a new dimension has evolved for com- munication amongst ...of detection of irony and sarcasm in textual data poses threat to the accuracy of the techniques evolved till ...a ... See full document

... machine learning methods, ...different deep-learning convolution neural networks (CNNs) for landslide ...created using ANN, SVM and RF and different CNN instantiations and are compared ... See full document

... However, deep learning algorithms such as convolutional neural networks and deep belief networks have proven to provide promising results in many research domains, ... See full document

... the method of similarity calculation models of actions, but it needs to complete the test verification in further ...the convolutional neural network is used to identify snake-like maneuvering images, but ... See full document

... crack detection method consisting of convolution feature extraction, dilated convolution receptive field expansion, multiscale max pooling, and skip con- nection of feature fusion ...resulting method ... See full document

... fact, using MFCC-like features followed by a CNN is widely applied to various audio classification problems, such as audio events ...without using zero ...a convolutional layer with 16 kernels sized ... See full document

... window method to extract multiple ...of convolutional neural systems, which were observed to be less demanding to prepare notwithstanding for more profound architectures ... See full document

... cancer using deep learning and some segmentation techniques are ...aided detection (CAD) system is proposed for classifying benign and malignant mass tumors in breast mammography ...The ... See full document

... neural networks (ANNs) with several hidden lay- ...(not deep) artificial neu- ral networks used for seizure detection, 25–29 the deep networks do not need any hand-designed ... See full document

... cancer using deep learning and some segmentation techniques are ...aided detection (CAD) system is proposed for classifying benign and malignant mass tumors in breast mammography ...The ... See full document

... Recently, deep learning technology is predominant method for plant diseases detection, especially deep convolutional neural networks (DCNN) [1, 2, ...most deep ... See full document

... VAD method, in which speech and non-speech models are trained on an utterance-by-utterance basis using mel-frequency cepstral coefficients ...a method based on a Gaussian statistical model, in which ... See full document

... a method to identify bot- nets in Android environment through model ...botnet detection system which exploits dynamic analysis by using a virtual environment with cluster ...botnet detection ... See full document

... years, deep learning techniques based on neural networks (NN) have set new performance standards for a wide variety of machine learning or computer vision ...these deep NNs are there ... See full document

... object detection have been taken care by Convolutional Neural Networks, which is a type of Deep Neural Network which was developed as similar as Human Visual system, Many CNN models was ... See full document

... reality. Deep learning methods have shown tremendous success for interpretation problems for which algorithmic methods have ...where deep learning approaches outperform traditional computer ... See full document