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    Deep Learning in Action: Image and Video  Processing for Practical Use

    Deep Learning in Action: Image and Video Processing for Practical Use by Elhanashi, Abdussalam; Saponara, Sergio;

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      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 140.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        59 807 Ft (56 959 Ft + 5% VAT)
      • Discount 10% (cc. 5 981 Ft off)
      • Discounted price 53 826 Ft (51 263 Ft + 5% VAT)

    59 807 Ft

    db

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    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Long description:

    Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.


    • Provides step-by-step guidance on implementing deep learning techniques, specifically for video and image processing tasks in real-world scenarios
    • Emphasizes lightweight and efficient approaches to deep learning, ensuring that readers learn techniques that are suited to resource-constrained environments
    • Covers a wide range of real-world applications, such as object detection, image segmentation, video classification
    • Offers a comprehensive understanding of how deep learning can be leveraged across various domains
    • Encourages hands-on experience that can be applied to the concepts to existing projects

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    Table of Contents:

    1. Introduction
    2. Image Analysis for Surveillance: Detecting Fire and Smoke Incidents
    3. Enhancing COVID-19 Safety Measures with AI-Powered Video Analysis
    4. Deep Learning Approaches for Fingerprint Image Restoration 4.1 Background
    5. Deep Learning for Classification and Localization of Multiple Abnormalities on chest x-rays images
    6. Real-time Stroke Detection Based on Deep Learning and Federated Learning
    7. Efficient Identification of Bag Breakup in Continuous Airflow via Video Analysis

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