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{ "item_title" : "Less-Supervised Segmentation with Cnns", "item_author" : [" Jose Dolz", "Ismail Ben Ayed", "Christian Desrosiers "], "item_description" : "Less-Supervised Segmentation with CNNs: Scenarios, Models and Optimization reviews recent progress in deep learning for image segmentation under scenarios with limited supervision, with a focus on medical imaging. The book presents main approaches and state-of-the-art models and includes a broad array of applications in medical image segmentation, including healthcare, oncology, cardiology and neuroimaging. A key objective is to make this mathematical subject accessible to a broad engineering and computing audience by using a large number of intuitive graphical illustrations. The emphasis is on giving conceptual understanding of the methods to foster easier learning. This book is highly suitable for researchers and graduate students in computer vision, machine learning and medical imaging.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/0/32/395/674/0323956742_b.jpg", "price_data" : { "retail_price" : "115.00", "online_price" : "115.00", "our_price" : "115.00", "club_price" : "115.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Less-Supervised Segmentation with Cnns|Jose Dolz

Less-Supervised Segmentation with Cnns : Scenarios, Models and Optimization

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Overview

Less-Supervised Segmentation with CNNs: Scenarios, Models and Optimization reviews recent progress in deep learning for image segmentation under scenarios with limited supervision, with a focus on medical imaging. The book presents main approaches and state-of-the-art models and includes a broad array of applications in medical image segmentation, including healthcare, oncology, cardiology and neuroimaging. A key objective is to make this mathematical subject accessible to a broad engineering and computing audience by using a large number of intuitive graphical illustrations. The emphasis is on giving conceptual understanding of the methods to foster easier learning.

This book is highly suitable for researchers and graduate students in computer vision, machine learning and medical imaging.

This item is Non-Returnable

Details

  • ISBN-13: 9780323956741
  • ISBN-10: 0323956742
  • Publisher: Academic Press
  • Publish Date: September 2025
  • Dimensions: 9.21 x 7.48 x 0.71 inches
  • Shipping Weight: 1.67 pounds
  • Page Count: 346

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