Deep Learning Video Image (32 results)

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Taschenbuch. Condition: Neu. Deep Learning Based Emotion Recognition for Image and Video Signals | Matlab Implementation | Arselan Ashraf (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203583564 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

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Condition: New. In English.

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Condition: New. Provides step-by-step guidance on implementing deep learning techniques, specifically for video and image processing tasks in real-world scenariosEmphasizes lightweight and efficient approaches to deep learning, ensuring that readers learn .

Condition: New. 2026. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

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Taschenbuch. Condition: Neu. Neuware - 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.…

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Emotion recognition utilizing pictures, videos, or speech as input is considered an intriguing issue in the research field over certain years. The introduction of deep learning procedures like the Convolutional Neural Networks (CNN) has made emotion recognition achieve promising outcomes. This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. Different pre-processing steps have been carried over data samples, followed by the popular and efficient Viola-Jones algorithm for face detection. Evaluating results using confusion matrix, accuracy, F1-score, precision, and recall shows that video-based datasets obtained more promising results than image-based datasets. 124 pp. Englisch.…

Hardcover. Condition: new. Hardcover. The Reprint titled "Deep Learning in Video and Image Processing Challenges Solutions and Future Directions" presents a comprehensive collection of high-quality research addressing the growing demand for intelligent visual systems operating in real time. This Reprint focuses on the practical deployment of deep learning and machine learning techniques for video and image processing on edge devices with limited computational resources. It highlights recent advances that enable efficient model execution under strict constraints related to power consumption memory capacity and processing speed. The Reprint covers a wide range of topics, including lightweight neural network architectures, algorithm optimization, hardware-software co design, and energy-efficient learning models. Emphasis is placed on real-world applications where low latency and on-device intelligence are critical, such as medical imaging, surveillance systems, autonomous driving, smart city monitoring, industrial automation, and wearable health devices. Unlike conventional cloud-based solutions, this Reprint promotes localized data processing to reduce latency enhance privacy and improve system reliability. By bridging theoretical research and practical implementations, the collected works provide valuable insights into scalable and deployable edge intelligence solutions. This Reprint serves as a key reference for researchers, engineers, and practitioners seeking to design robust real-time visual processing systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Ashraf ArselanArselan Arshaf obtained his MSc degree from IIUM in 2021. Teddy Surya Gunawan received his PhD degree from UNSW in 2007 and is currently Professor at KOE, IIUM. Mira Kartiwi obtained her PhD from UOW in 2009 and is curr. …

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Emotion recognition utilizing pictures, videos, or speech as input is considered an intriguing issue in the research field over certain years. The introduction of deep learning procedures like the Convolutional Neural Networks (CNN) has made emotion recognition achieve promising outcomes. This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. Different pre-processing steps have been carried over data samples, followed by the popular and efficient Viola-Jones algorithm for face detection. Evaluating results using confusion matrix, accuracy, F1-score, precision, and recall shows that video-based datasets obtained more promising results than image-based datasets.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Emotion recognition utilizing pictures, videos, or speech as input is considered an intriguing issue in the research field over certain years. The introduction of deep learning procedures like the Convolutional Neural Networks (CNN) has made emotion recognition achieve promising outcomes. This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. Different pre-processing steps have been carried over data samples, followed by the popular and efficient Viola-Jones algorithm for face detection. Evaluating results using confusion matrix, accuracy, F1-score, precision, and recall shows that video-based datasets obtained more promising results than image-based datasets.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch.…

Hardcover. Condition: new. Hardcover. The Reprint titled "Deep Learning in Video and Image Processing Challenges Solutions and Future Directions" presents a comprehensive collection of high-quality research addressing the growing demand for intelligent visual systems operating in real time. This Reprint focuses on the practical deployment of deep learning and machine learning techniques for video and image processing on edge devices with limited computational resources. It highlights recent advances that enable efficient model execution under strict constraints related to power consumption memory capacity and processing speed. The Reprint covers a wide range of topics, including lightweight neural network architectures, algorithm optimization, hardware-software co design, and energy-efficient learning models. Emphasis is placed on real-world applications where low latency and on-device intelligence are critical, such as medical imaging, surveillance systems, autonomous driving, smart city monitoring, industrial automation, and wearable health devices. Unlike conventional cloud-based solutions, this Reprint promotes localized data processing to reduce latency enhance privacy and improve system reliability. By bridging theoretical research and practical implementations, the collected works provide valuable insights into scalable and deployable edge intelligence solutions. This Reprint serves as a key reference for researchers, engineers, and practitioners seeking to design robust real-time visual processing systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Condition: new. Questo è un articolo print on demand.

Paperback. Condition: Brand New. 250 pages. 9.25x7.50x0.40 inches. In Stock. This item is printed on demand.

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The Reprint titled 'Deep Learning in Video and Image Processing Challenges Solutions and Future Directions' presents a comprehensive collection of high-quality research addressing the growing demand for intelligent visual systems operating in real time. This Reprint focuses on the practical deployment of deep learning and machine learning techniques for video and image processing on edge devices with limited computational resources. It highlights recent advances that enable efficient model execution under strict constraints related to power consumption memory capacity and processing speed. The Reprint covers a wide range of topics, including lightweight neural network architectures, algorithm optimization, hardware-software co design, and energy-efficient learning models. Emphasis is placed on real-world applications where low latency and on-device intelligence are critical, such as medical imaging, surveillance systems, autonomous driving, smart city monitoring, industrial automation, and wearable health devices. Unlike conventional cloud-based solutions, this Reprint promotes localized data processing to reduce latency enhance privacy and improve system reliability. By bridging theoretical research and practical implementations, the collected works provide valuable insights into scalable and deployable edge intelligence solutions. This Reprint serves as a key reference for researchers, engineers, and practitioners seeking to design robust real-time visual processing systems.…