Machine Learning in Medical Imaging and Computer Vision
portes grátis
Machine Learning in Medical Imaging and Computer Vision
Zhou, Liang; Ganchev, Todor; Dhaka, Arvind; Nait-Abdesselam, Farid; Nandal, Amita
Institution of Engineering and Technology
01/2024
382
Dura
Inglês
9781839535932
15 a 20 dias
Descrição não disponível.
Chapter 1: Machine learning algorithms and applications in medical imaging processing
Chapter 2: Review of deep learning methods for medical segmentation tasks in brain tumors
Chapter 3: Optimization algorithms and regularization techniques using deep learning
Chapter 4: Computer-aided diagnosis in maritime healthcare: review of spinal hernia
Chapter 5: Diabetic retinopathy detection using AI
Chapter 6: A survey image classification using convolutional neural network in deep learning
Chapter 7: Text recognition using CRNN models based on temporal classification and interpolation methods
Chapter 8: Microscopic Plasmodium classification (MPC) using robust deep learning strategies for malaria detection
Chapter 9: Medical image classification and retrieval using deep learning
Chapter 10: Game theory, optimization algorithms and regularization techniques using deep learning in medical imaging
Chapter 11: Data preparation for artificial intelligence in federated learning: the influence of artifacts on the composition of the mammography database
Chapter 12: Spatial cognition by the visually impaired: image processing with SIFT/BRISK-like detector and two-keypoint descriptor on Android CameraX
Chapter 13: Feature extraction process through hypergraph learning with the concept of rough set classification
Chapter 14: Machine learning for neurodegenerative disease diagnosis: a focus on amyotrophic lateral sclerosis (ALS)
Chapter 15: Using deep/machine learning to identify patterns and detecting misinformation for pandemics in the post-COVID-19 era
Chapter 16: Integrating medical imaging using analytic modules and applications
Chapter 2: Review of deep learning methods for medical segmentation tasks in brain tumors
Chapter 3: Optimization algorithms and regularization techniques using deep learning
Chapter 4: Computer-aided diagnosis in maritime healthcare: review of spinal hernia
Chapter 5: Diabetic retinopathy detection using AI
Chapter 6: A survey image classification using convolutional neural network in deep learning
Chapter 7: Text recognition using CRNN models based on temporal classification and interpolation methods
Chapter 8: Microscopic Plasmodium classification (MPC) using robust deep learning strategies for malaria detection
Chapter 9: Medical image classification and retrieval using deep learning
Chapter 10: Game theory, optimization algorithms and regularization techniques using deep learning in medical imaging
Chapter 11: Data preparation for artificial intelligence in federated learning: the influence of artifacts on the composition of the mammography database
Chapter 12: Spatial cognition by the visually impaired: image processing with SIFT/BRISK-like detector and two-keypoint descriptor on Android CameraX
Chapter 13: Feature extraction process through hypergraph learning with the concept of rough set classification
Chapter 14: Machine learning for neurodegenerative disease diagnosis: a focus on amyotrophic lateral sclerosis (ALS)
Chapter 15: Using deep/machine learning to identify patterns and detecting misinformation for pandemics in the post-COVID-19 era
Chapter 16: Integrating medical imaging using analytic modules and applications
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medical image processing; computer vision; deep learning (artificial intelligence); image classification; tumours; diseases; convolutional neural nets; feature extraction
Chapter 1: Machine learning algorithms and applications in medical imaging processing
Chapter 2: Review of deep learning methods for medical segmentation tasks in brain tumors
Chapter 3: Optimization algorithms and regularization techniques using deep learning
Chapter 4: Computer-aided diagnosis in maritime healthcare: review of spinal hernia
Chapter 5: Diabetic retinopathy detection using AI
Chapter 6: A survey image classification using convolutional neural network in deep learning
Chapter 7: Text recognition using CRNN models based on temporal classification and interpolation methods
Chapter 8: Microscopic Plasmodium classification (MPC) using robust deep learning strategies for malaria detection
Chapter 9: Medical image classification and retrieval using deep learning
Chapter 10: Game theory, optimization algorithms and regularization techniques using deep learning in medical imaging
Chapter 11: Data preparation for artificial intelligence in federated learning: the influence of artifacts on the composition of the mammography database
Chapter 12: Spatial cognition by the visually impaired: image processing with SIFT/BRISK-like detector and two-keypoint descriptor on Android CameraX
Chapter 13: Feature extraction process through hypergraph learning with the concept of rough set classification
Chapter 14: Machine learning for neurodegenerative disease diagnosis: a focus on amyotrophic lateral sclerosis (ALS)
Chapter 15: Using deep/machine learning to identify patterns and detecting misinformation for pandemics in the post-COVID-19 era
Chapter 16: Integrating medical imaging using analytic modules and applications
Chapter 2: Review of deep learning methods for medical segmentation tasks in brain tumors
Chapter 3: Optimization algorithms and regularization techniques using deep learning
Chapter 4: Computer-aided diagnosis in maritime healthcare: review of spinal hernia
Chapter 5: Diabetic retinopathy detection using AI
Chapter 6: A survey image classification using convolutional neural network in deep learning
Chapter 7: Text recognition using CRNN models based on temporal classification and interpolation methods
Chapter 8: Microscopic Plasmodium classification (MPC) using robust deep learning strategies for malaria detection
Chapter 9: Medical image classification and retrieval using deep learning
Chapter 10: Game theory, optimization algorithms and regularization techniques using deep learning in medical imaging
Chapter 11: Data preparation for artificial intelligence in federated learning: the influence of artifacts on the composition of the mammography database
Chapter 12: Spatial cognition by the visually impaired: image processing with SIFT/BRISK-like detector and two-keypoint descriptor on Android CameraX
Chapter 13: Feature extraction process through hypergraph learning with the concept of rough set classification
Chapter 14: Machine learning for neurodegenerative disease diagnosis: a focus on amyotrophic lateral sclerosis (ALS)
Chapter 15: Using deep/machine learning to identify patterns and detecting misinformation for pandemics in the post-COVID-19 era
Chapter 16: Integrating medical imaging using analytic modules and applications
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
