Titlebook: Deep Learning Applications in Image Analysis; Sanjiban Sekhar Roy,Ching-Hsien Hsu,Venkateshwara Book 2023 The Editor(s) (if applicable) a

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2197-6503 ons in medical, satellite, forensic image analysis.DemonstraThis book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algor

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Klaus-Dieter Schewe,Bernhard Thalheimia using Image Recognition based deep learning algorithms. This chapter aims to solve this problem using novel machine learning frameworks involving the Efficient-Net and InceptionV3 algorithms to achieve this goal. Our proposed models have achieved an accuracy of 92.93% via the InceptionV3 model and 95.39% via the EfficientNet model.

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Book 2023hat can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten

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https://doi.org/10.1007/978-1-349-02787-3ins five types of captions. At first, we extracted features from the images using CNN. Subsequently these features are trained through transfer learning. Subsequently a RNN is used as a decoder for generating the language text. The trained model performs better for other datasets also.

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Polymorphism in Carbons and Parent Materialse balanced datasets, ResNet-50 has yielded 97.95% and 97.92% test accuracy, respectively whereas the test accuracy on the original dataset has been 97.63%. These methods can help us to obtain a robust Bangla handwritten classifier.

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https://doi.org/10.1007/978-1-349-02787-3y tracing based on video surveillance in public places, and show how it can be used in different scenarios ranging from individual contact tracing or epidemiological surveillance of crowds to the improved public spaces planning.