Efficacy of deep convolutional neural network algorithm for the identification and classification of dental implant systems, using panoramic and periapical radiographs: A pilot study Medicine (Baltimore), 99 (2020), p. 20787 Google Scholar 6 R. Santos, H. Prado, I. Neto, et al. Automated identi...
To confirm reproducibility, each model and algorithm were trained 10 times with different random seeds. F1 scores were 0.67 ± 0.03 (CTG-net), 0.66 ± 0.04 (LSTM), 0.55 ± 0.05 (SVM), and 0.52 ± 0.12 (k-means clustering). The performances of both DNN models ...
Twitter Google Share on Facebook conventional algorithm [kən′ven·chən·əl ′al·gə‚rith·əm] (communications) A cryptographic algorithm in which the enciphering and deciphering keys are easily derivable from each other, or are identical, and both must be kept secret. ...
images from the CT volume scanned for a longer duration by tracing the root segments using RSAvis3D and RSAtrace3D software (Fig.1c). RSAvis3D enriched root features using an edge detection algorithm [20], thereby enabling RSAtrace3D to produce an RSA vector to generate RSA segmentation. Fi...
As a type of artificial intelligence, a machine-learning (ML) algorithm builds a model based on a training dataset and can improve its performance with experience. ML is anticipated to be a tool for predicting individualized diagnoses and clinical outcomes, as it is more accurate and precise tha...
In this paper an Artificial Neural Network (ANN) algorithm is presented in order to solve the problems associated with the conventional DTC approach. In order to improve the performances of the DTC controlled PMSM and to reject the disturbances, an ANN algorithm is used. This intelligent artificia...
In the present study, we introduce new bubble velocimetry methods based on the optical flow, which were validated (compared) with the conventional particle tracking velocimetry (PTV) for various gas–liquid two-phase flows. For the optical flow algorithm
To improve the exploration efficiency of the deep reinforcement learning algorithm, a random network distillation technique is used. A multi-objective reward function containing an external reward and an additional internal reward is designed. Finally, simulation results show that, compared with the ...
Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model Energy, 118 (2017), pp. 231-245 View PDFView articleView in ScopusGoogle Scholar Pao, 2009 H.T. Pao Forecasting energy consumption in Taiwan using hybrid nonline...
In the biomedical image analysis context, this approach has been proposed in ML-assisted diagnostic tools for hospitals where the algorithm performance degrades over time. The root cause in many cases is the expected changes in local data, such as data acquisition pipelines and population shifts, ...