Titlebook: Computational Signal Processing and Analysis; Select Proceedings o Asoke K. Nandi,N Sujatha,John Sahaya Rani Alex Conference proceedings 20

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書目名稱Computational Signal Processing and Analysis影響因子(影響力)




書目名稱Computational Signal Processing and Analysis影響因子(影響力)學(xué)科排名




書目名稱Computational Signal Processing and Analysis網(wǎng)絡(luò)公開度




書目名稱Computational Signal Processing and Analysis網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Signal Processing and Analysis被引頻次




書目名稱Computational Signal Processing and Analysis被引頻次學(xué)科排名




書目名稱Computational Signal Processing and Analysis年度引用




書目名稱Computational Signal Processing and Analysis年度引用學(xué)科排名




書目名稱Computational Signal Processing and Analysis讀者反饋




書目名稱Computational Signal Processing and Analysis讀者反饋學(xué)科排名

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復(fù)習(xí)

https://doi.org/10.1007/978-981-13-0623-5of the smart plate. The finite element model is reduced to the first three modes using orthonormal modal truncation, and subsequently, the reduced finite element model is converted into a state-space model.

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A Comparative Study of Isolated Word Recognizer Using SVM and WaveNet,racy of classification for WaveNets is shown in the results. The number of features is also varied using dimension reduction technique and its effect on the accuracies is studied. The data is prepared using feature scaling and dimensionality reduction before training SVM and NN classifiers.

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https://doi.org/10.1007/978-3-642-34375-9aged FFT, location averaged DCT, and location averaged DWT are the three methods proposed for face and ear recognition system. The standard face and ear database images are used for analyzing the accuracy, runtime, and mismatching. The maximum accuracy value of about 99% is achieved in shortest run time with less mismatching.

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Grzegorz Sierpiński,Ireneusz Celiński Jones proposed a fast and accurate method to detect the object. Haar-like features are used to detect the variation between the black and light portion of the image. Cam-shift algorithm is used to develop the face and head tracking. The object search is done using the back-projection procedure through probability distribution maximum obtained.

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