Results 291 to 300 of about 336,714 (315)

Speech Emotion Recognition using MFCC, GFCC, Chromagram and RMSE features

2021 8th International Conference on Signal Processing and Integrated Networks (SPIN), 2021
In recent years, increasing attention is given to the research of the emotions present in speech. Various systems are developed aiming to detect the emotions in the speaker’s statements. One of the biggest differences between a machine and a human is understanding the emotions of others and behaving accordingly. Researchers are working on bridging this
Hrithik Patni, Akash Jagtap, Vaishali Bhoyar, Aditya Gupta   +3 more
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RMSE calculation of LSTM models for predicting prices of different cryptocurrencies

International Journal of System Assurance Engineering and Management, 2021
Cryptocurrencies are becoming popular day by day and their use in financial applications has also increased; hence they are recognized as a method for payments. For decades, trading in cryptocurrency has been popular and constantly increasing in financial markets; hence investors are looking forward to their positive returns through these ...
Nitima Malsa, Vaibhav Vyas, Jyoti Gautam
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Fast Fractal Image Coding Method Based on RMSE and DCT Classification

Applied Mechanics and Materials, 2012
To solve the problem of long time consuming in the fractal encoding process, a fast fractal encoding algorithm based on RMSE (Root mean square error) and DCT (Discrete Cosine Transform) classification is proposed. During the encoding process, firstly, the image is divided into range blocks and domain blocks by quadtree partition according to RMSE, then,
Xian Qiang Lv, Song Yang, Xin Zhang, Ying Wang, Yun Feng Shi, Liu Wei   +5 more
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SRG and RMSE-Based Automated Segmentation for Volume Data

2017
Feature visualization plays an important role in volume visualization as it can alleviate the existing problems in direct volume rending. While extraction of the predefined features is also an issue which is difficult to solve. Volume segmentation is of great significance for feature visualization as it is pre-processing of feature extraction ...
Wang Li, Xiaoan Tang, Junda Zhang
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PENERAPAN METODE K-NEAREST NEIGHBOR UNTUK PREDIKSI HARGA JAGUNG DENGAN PENGUJIAN RMSE

JATI (Jurnal Mahasiswa Teknik Informatika), 2023
Jagung merupakan salah satu komoditas pertanian yang penting di Indonesia, baik sebagai bahan pangan maupun sebagai bahan industri. Namun, pada tahun 2022, produksi jagung mengalami penurunan menjadi sebesar 339.788,4 ton, sedangkan untuk permintaan jagung pada tahun 2022 sebesar 36.527 ton dan penawaran sebesar 298.508 ton.
Sandy Tri Wijaya, Indyah Hartami Santi, Zunita Wulansari   +2 more
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Clustering Analysis to Improve Web Search Ranking Using PCA and RMSE

2020
Classification of web pages is the first step of web page ranking (or we can call it indexing), one of the most common ways to achieve indexing process is clustering that pages into groups as per the similarity, whenever the misclassification is less, the result will be perfect. Moreover, clustering is a collection of algorithms that dive the data into
Mohammed A. Ko’adan, Mohammed A. Bamatraf, Khalid Q. Shafal   +2 more
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Bias And RMSE of Archimedean Copula using Moment And L-Moments Methods

2020 2nd International Conference on Mathematics and Information Technology (ICMIT), 2020
In this paper we are concerned by a semiparametric estimation of Archimedean copulas models, two methods are mentioned, the method of moments and L-moments, recently developed by Brahimi et. al. (2012), Benatia et. al.(2012) whose advantage is to be valid even for nonexistent or infinite moments distributions.
Nesrine Idiou, Fatah Benatia, Brahim Brahimi   +2 more
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Is average RMSE appropriate for evaluating acoustic-to-articulatory inversion?

2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019
Acoustic-to-articulatory inversion has potential application in number of fields. For decades, average root mean square error and Pearson correlation coefficient are the most prevalent quantities adopted to evaluate the performance of acoustic-to-articulatory inversion.
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