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[ subject:"Image analysis- Data processing." ]
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Deep learning-based image analysis u...
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Raj, Alex Noel Joseph, (1979-)
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Deep learning-based image analysis under constrained and unconstrained environments
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Deep learning-based image analysis under constrained and unconstrained environments/ Alex Noel Joseph Raj, Vijayalakshmi G.V. Mahesh and Nersisson Ruban, editors.
其他作者:
Raj, Alex Noel Joseph,
出版者:
Hershey, Pennsylvania :IGI Global, : 2021.,
面頁冊數:
1 online resource (xxi, 381 p.)
內容註:
Chapter 1. Computer processing of an image: an introduction -- Chapter 2. Brain tumor detection and classification based on histogram equalization using machine learning -- Chapter 3. Breast ultrasound image processing -- Chapter 4. Layer-wise tumor segmentation of breast images using convolutional neural networks -- Chapter 5. Breast cancer detection using random forest classifier -- Chapter 6. Pulomonary nodule classification from CT scan images using machine learning method -- Chapter 7. Segmentation of optic disc from fundus image based on morphology and SVM classifier -- Chapter 8. Performance analysis of VGG19 deep learning network based brain image fusion -- Chapter 9. Apple leaf disease identification based on optimized deep neural network -- Chapter 10. A new approach of deep learning-based Tamil vowels prediction using segmentation and U-net architecture -- Chapter 11. Edge enhancement method for detection of text from handwritten documents -- Chapter 12. A deep learning-based framework for accurate facial ethnicity classification and efficient query retrieval -- Chapter 13. Finding facial emotions from the clutter scenes using Zernike moments-based convolutional neural networks -- Chapter 14. Facial expression: psychophysiological study -- Chapter 15. Performance analysis of GAN architecture for effective facial expression synthesis -- Chapter 16. Deep convolutional neural network for object classification: under constrained and unconstrained environments.
標題:
Image analysis - Data processing. -
電子資源:
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-6690-9
ISBN:
9781799866923 (ebk.)
Deep learning-based image analysis under constrained and unconstrained environments
Deep learning-based image analysis under constrained and unconstrained environments
[electronic resource] /Alex Noel Joseph Raj, Vijayalakshmi G.V. Mahesh and Nersisson Ruban, editors. - Hershey, Pennsylvania :IGI Global,2021. - 1 online resource (xxi, 381 p.)
Includes bibliographical references and index.
Chapter 1. Computer processing of an image: an introduction -- Chapter 2. Brain tumor detection and classification based on histogram equalization using machine learning -- Chapter 3. Breast ultrasound image processing -- Chapter 4. Layer-wise tumor segmentation of breast images using convolutional neural networks -- Chapter 5. Breast cancer detection using random forest classifier -- Chapter 6. Pulomonary nodule classification from CT scan images using machine learning method -- Chapter 7. Segmentation of optic disc from fundus image based on morphology and SVM classifier -- Chapter 8. Performance analysis of VGG19 deep learning network based brain image fusion -- Chapter 9. Apple leaf disease identification based on optimized deep neural network -- Chapter 10. A new approach of deep learning-based Tamil vowels prediction using segmentation and U-net architecture -- Chapter 11. Edge enhancement method for detection of text from handwritten documents -- Chapter 12. A deep learning-based framework for accurate facial ethnicity classification and efficient query retrieval -- Chapter 13. Finding facial emotions from the clutter scenes using Zernike moments-based convolutional neural networks -- Chapter 14. Facial expression: psychophysiological study -- Chapter 15. Performance analysis of GAN architecture for effective facial expression synthesis -- Chapter 16. Deep convolutional neural network for object classification: under constrained and unconstrained environments.
"This book attempts to provide an overview of image analysis based on deep learning methods and their applications, allowing readers to learn and explore the latest advancements, developments, methods, systems, futuristic approaches and algorithms towards image analysis"--
ISBN: 9781799866923 (ebk.)Subjects--Topical Terms:
734977
Image analysis
--Data processing.
LC Class. No.: TA1637 / .H36 2021
Dewey Class. No.: 621.36/70285631
Deep learning-based image analysis under constrained and unconstrained environments
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Chapter 1. Computer processing of an image: an introduction -- Chapter 2. Brain tumor detection and classification based on histogram equalization using machine learning -- Chapter 3. Breast ultrasound image processing -- Chapter 4. Layer-wise tumor segmentation of breast images using convolutional neural networks -- Chapter 5. Breast cancer detection using random forest classifier -- Chapter 6. Pulomonary nodule classification from CT scan images using machine learning method -- Chapter 7. Segmentation of optic disc from fundus image based on morphology and SVM classifier -- Chapter 8. Performance analysis of VGG19 deep learning network based brain image fusion -- Chapter 9. Apple leaf disease identification based on optimized deep neural network -- Chapter 10. A new approach of deep learning-based Tamil vowels prediction using segmentation and U-net architecture -- Chapter 11. Edge enhancement method for detection of text from handwritten documents -- Chapter 12. A deep learning-based framework for accurate facial ethnicity classification and efficient query retrieval -- Chapter 13. Finding facial emotions from the clutter scenes using Zernike moments-based convolutional neural networks -- Chapter 14. Facial expression: psychophysiological study -- Chapter 15. Performance analysis of GAN architecture for effective facial expression synthesis -- Chapter 16. Deep convolutional neural network for object classification: under constrained and unconstrained environments.
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http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/978-1-7998-6690-9
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