Search Results - (( using convolutional network algorithm ) OR ( data classification methods algorithm ))

An efficient algorithm for cardiac arrhythmia classification using ensemble of depthwise Separable convolutional neural networks by Ihsanto, Eko, Ramli, Kalamullah, Sudiana, Dodi, Gunawan, Teddy Surya

“…This paper proposed a novel method, i.e., the ensemble of depthwise separable convolutional (DSC) neural networks for the classification of cardiac arrhythmia ECG beats. …”
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Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

“…Besides, the convolutional neural network (CNN) was implemented and combined with the RBF algorithm for the ASD classification. …”
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Sentiment analysis of hotel reviews using Convolutional Neural Network / Sofea Aini Mohd Sufian by Mohd Sufian, Sofea Aini

“…The prototype also been implemented using CNN model to predict the sentiment on hotel review, hi conclusion, the CNN algorithm can be used as text classification as it gives a high accuracy.…”
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Lung Nodules Classification Using Convolutional Neural Network with Transfer Learning by Abdulrazak Yahya, Saleh, Ros Ameera, Rosdi

“…Convolutional neural network (CNN), one of the deep neural network methods, has had a significant impact in the field of computer vision. …”
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Task-state EEG signal classification for spatial cognitive evaluation based on multiscale high-density convolutional neural network by Wen, Dong, Li, Rou, Tang, Hao, Liu, Yijun, Wan, Xianglong, Dong, Xianling, Saripan, M. Iqbal, Lan, Xifa, Song, Haiqing, Zhou, Yanhong

“…In this study, a multi-scale high-density convolutional neural network (MHCNN) classification method for spatial cognitive ability assessment was proposed, aiming at achieving the binary classification of task-state EEG signals before and after spatial cognitive training. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm by Ismail, Asmida, Ahmad, Siti Anom, Che Soh, Azura, Hassan, Mohd Khair, Harith, Hazreen Haizi

“…MiniVGGNet is an architecture network used to train an object classification, and the data used for this purpose was collected from specific indoor environment building. …”
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Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion by Zafar, R., Dass, S.C., Malik, A.S.

“…In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. …”
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Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

“…In this study, an algorithm is developed using Multivariate pattern analysis (MVPA) and modified CNN to decode the behavior of brain for different images with limited data set. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Transfer Learning for Lung Nodules Classification with CNN and Random Forest by Abdulrazak Yahya, Saleh, Chee, Ka Chin, Ros Ameera, Rosdi

“…This research aims include preprocessing lung nodular data, developing the proposed algorithm, and comparing its effectiveness with other methods. …”
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Image Splicing Detection With Constrained Convolutional Neural Network by Lee, Yang Yang

“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…A Convolutional Neural Network (CNN) model was created from scratch for this study. …”
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A novel architecture to verify offline hand-written signatures using convolutional neural network by Alkaabi S., Yussof S., Almulla S., Al-Khateeb H., Alabdulsalam A.A.

Object detection utilizing modified auto encoder and convolutional neural networks by Khiarak, Jalil Nourmohammadi, Mazaheri, Samaneh, Tayebi, Rohollah Moosavi, Noorbakhsh-Devlagh, Hamid

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Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain by Hakim M., Omran A.A.B., Inayat-Hussain J.I., Ahmed A.N., Abdellatef H., Abdellatif A., Gheni H.M.

Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

“…The accuracy of 2D tumor detection and segmentation are increased, enabling more 3D detection, and achieving a mean classification accuracy of 98 across system records. Finally, a hybrid approach of GoogLeNet deep learning algorithm and Convolution Neural Network- Support Vector Machines (CNN-SVM) deep learning is performed to increase the accuracy of tumor classification. …”
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Unsupervised classification of multi-class chart images: A comparison of customized CNNs and transfer learning techniques by Hassan Zaidi, Syed Muhammad, Jamil Alsayaydeh, Jamil Abedalrahim, Khan, Abdul Hafeez, Khan, Abdullah Ayub, AlZubi, Ahmad Ali, Ogunshola, Benny, Herawan, Safarudin Gazali

“…For classification, three pre-trained models, Residual Network 50 (ResNet50), Residual Network 50 Version 2 (ResNet50V2), and Densely Connected Convolutional Network (DenseNet) are evaluated alongside a customized convolutional neural network (CNN) using the ChartVQA dataset. …”
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Classification of atrial fibrillation with pretrained convolutional neural network models by Qayyum, A., Meriaudeau, F., Chan, G.C.Y.

“…The pre-trained CNN models are used for transfer learning or are fine tuned for the detection and classification of the AF rhythm. The features extracted from the last layer of the pre-trained models are used as input to classical classification algorithms such as Ensemble classifier and support vector machine (SVM) for AF detection. …”
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Finger-Vein Biometric Identification Using Convolutional Neural Network by Syafeeza, Ahmad Radzi, Mohamed, Khalil-Hani, Rabia, Bakhteri

“…A novel approach using a convolutional neural network (CNN) for finger-vein biometric identification is presented in this paper. …”
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