Titlebook: Advances in Data-driven Computing and Intelligent Systems; Selected Papers from Swagatam Das,Snehanshu Saha,Jagdish Chand Bansal Conference

Abrupt

Sherry A. Southerland,Sibel Uysal Bahbahnswer. The Bilingual Evaluation Understudy score is utilized as a metric for analyzing the efficiency of the framework. The BLEU is calculated by comparing a candidate text translation against reference translations. BLEU 1-gram, 2-gram, and 3-gram scores have been analyzed for evaluating the perfor

使虛弱

M.-H. Chiu,P. J. Gilmer,D. F. Treagustl features are extracted from mel-spectrograms in terms of flatten vectors (FVs) by utilizing a pre-trained DCNN model (VGG-16 model). The machine learning models that are considered for the hard voting ensemble approach are random forest (RF), extreme gradient boosting (XGBoost) and support vector

Harpoon

Désiré Baloubi,Christina R. Pinkstonrivate health data are generally in the form of real-time entities like disease information, health and physical attributes like height and weight of a person, and so on. Therefore, the sensitive health entities in social media were identified by the novel Principal Sensitive Health Entity Extractio

Mere僅僅

GLUE

https://doi.org/10.1007/978-3-030-50797-8to improve the accuracy metrics. A comparison of ResNet-50, Efficient Net B3, MobileNetV2 individual, and Stacking ensemble of these architectures was investigated in terms of AUC, accuracy, specificity, and sensitivity. Result shows that ResNet-50 has better AUC, accuracy, sensitivity, and specific

minion

ineptitude

Modeling of Ladle Metallurgy in Steelmaking cloud systems. However, modeling and simulation tools are often viable alternatives to cloud computing environment emulation. There are numerous simulation programs available, and they all have different features and applications. As a contribution to knowledge, in this paper, we first present a br

擴(kuò)大

Scenario-Based Neural Network Model for Integrated Lighting Schemes in Residential Buildings,978-1-4039-8212-4

物質(zhì)

Electrical Muscle Stimulation Models Identification Based on Hammerstein Structure and Gravitationa978-0-230-59909-3

宏偉