Titlebook: Concepts and Real-Time Applications of Deep Learning; Smriti Srivastava,Manju Khari,Parul Arora Book 2021 The Editor(s) (if applicable) an

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https://doi.org/10.1007/978-1-4419-8249-0a considerably sound knowledge base of social science, psychology, and anthropology that helps to train the machine. In this chapter, analysis and classification of speech for emotion recognition is done on RAVDESS dataset. Features are being extracted from speech utterances using Mel-frequency ceps

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Synchrotron Radiation and Astrophysics, this paper, Mel-frequency cepstral coefficients (MFCC) were extracted from the audio files. These features were then fed a convolutional neural network (CNN). This CNN was then optimized in order to increase model accuracy. Over the span of six runs of varying parameters, a maximum accuracy of appr

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Shock Waves in General Relativity, was noted. Six different models have been mentioned in this paper, and out of all the approaches performed, the multilayer perceptron neural network performed the best, having an average accuracy of 70.65% on three different input variations.

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General Relativity and Quantum Theory, from a video for recognition. The optical flow method was also used with neural networks for their detection. Nowadays, apex frame within a video frame is being used for the spatial-temporal credit, and the 3DCNN model is also being used. This chapter explains the Main Directional Maximal Different

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Matthew M. Peet,Catherine Bonnet,Hitay ?zbayed to forecast probable recovery. A common statistical approach used for this purpose is known as the Kaplan-Meier analysis. Survival predictability has become integral to the facilitation of patient care and resource optimization. This paper aims to provide an alternative survivability assessment u

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The Permeability of Abnormal Skin,ion while generating inferences and argue that a simpler framework with intelligent optimisation is able to successfully achieve higher performance metrics. We show how vivid attention plots can provide deep insight into the region of the image on which the network concentrates to generate a word to

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