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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Book 2021itectures;.Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies;.Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches..

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MELD

anticipate

Text-Independent Speaker Recognition Using Deep Learning 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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Emotion Recognition from Speech Signals Using Machine Learning and Deep Learning Techniques 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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A Low-Cost IOT and Deep Learning Enabled Precision Agriculture Support System for Indian Diverse Envnetwork (NN)-based small squeeze-and-excitation (SE) block residual network module with 50 layers (SE-Resnet50). In experimentation, convolutional neural network (CNN), residual neural network-50 (ResNet50), and SE-Resnet50 model are trained with 24,360 images of tomato plant leaves and 17,134 image