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Deep learning in computer vision : principles and applications / dited by Mahmoud Hassaballah, Ali Ismail Awad.

Contributor(s): Material type: TextTextPublisher: Boca Raton, FL : CRC Press, 2020Edition: First editionDescription: 322 pages : illustrations ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781032242859
Subject(s): DDC classification:
  • 23 006.37  D.E.E
Contents:
Chapter 1: Accelerating the CNN Inference on FPGAs -- Chapter 2: Object Detection with Convolutional Neural Networks -- Chapter 3: Efficient Convolutional Neural Networks for Fire Detection in Surveillance Applications -- Chapter 4: A Multi-biometric Face Recognition System Based on Multimodal Deep Learning Representations -- Chapter 5: Deep LSTM‑Based Sequence Learning Approaches for Action and Activity Recognition -- Chapter 6: Deep Semantic Segmentation in Autonomous Driving -- Chapter 7: Aerial Imagery Registration Using Deep Learning for UAV Geolocalization -- Chapter 8: Applications of Deep Learning in Robot Vision -- Chapter 9: Deep Convolutional Neural Networks: Foundations and Applications in Medical Imaging -- Chapter 10: Lossless Full‑Resolution Deep Learning Convolutional Networks for Skin Lesion Boundary Segmentation -- Chapter 11: Skin Melanoma Classification Using Deep Convolutional Neural Networks.
Summary: A collection of eleven focused chapters providing comprehensive coverage on how deep learning advances are applied to solve computer vision challenges—from accelerating CNN on FPGAs to medical imaging segmentation—designed as a valuable resource for researchers and graduate students.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books Books Media and mass communication Library C1 006.37 D.E.E Available MA0002654
Total holds: 0

Includes index.

Chapter 1: Accelerating the CNN Inference on FPGAs -- Chapter 2: Object Detection with Convolutional Neural Networks -- Chapter 3: Efficient Convolutional Neural Networks for Fire Detection in Surveillance Applications -- Chapter 4: A Multi-biometric Face Recognition System Based on Multimodal Deep Learning Representations -- Chapter 5: Deep LSTM‑Based Sequence Learning Approaches for Action and Activity Recognition -- Chapter 6: Deep Semantic Segmentation in Autonomous Driving -- Chapter 7: Aerial Imagery Registration Using Deep Learning for UAV Geolocalization -- Chapter 8: Applications of Deep Learning in Robot Vision -- Chapter 9: Deep Convolutional Neural Networks: Foundations and Applications in Medical Imaging -- Chapter 10: Lossless Full‑Resolution Deep Learning Convolutional Networks for Skin Lesion Boundary Segmentation -- Chapter 11: Skin Melanoma Classification Using Deep Convolutional Neural Networks.

A collection of eleven focused chapters providing comprehensive coverage on how deep learning advances are applied to solve computer vision challenges—from accelerating CNN on FPGAs to medical imaging segmentation—designed as a valuable resource for researchers and graduate students.

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