Deep Learning Algorithms
- Indbinding:
- Hardback
- Sideantal:
- 408
- Udgivet:
- 30. December 2021
- Størrelse:
- 152x229x0 mm.
- Vægt:
- 883 g.
- Ukendt - mangler pt..
Normalpris
Abonnementspris
- Rabat på køb af fysiske bøger
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af Deep Learning Algorithms
This book covers different topics from deep learning algorithms, including: methods and approaches for deep learning, deep learning applications in biology, deep learning applications in medicine, and deep learning applications in pattern recognition systems. Section 1 focuses on methods and approaches for deep learning, describing advancements in deep learning theory and applications - perspective in 2020 and beyond; deep ensemble reinforcement learning with multiple deep deterministic policy gradient algorithm; dynamic decision-making for stabilized deep learning software platforms; deep learning for hyperspectral data classification through exponential momentum deep convolution neural networks; and ensemble network architecture for deep reinforcement learning. Section 2 focuses on deep learning applications in biology, describing fish detection using deep learning; deep learning identification of tomato leaf disease; deep learning for plant identification in natural environment; and applying deep learning models to mouse behavior recognition. Section 3 focuses on deep learning applications in medicine, describing application of deep learning in neuroradiology: brain hemorrhage classification using transfer learning; a review of the application of deep learning in brachytherapy; exploring deep learning and transfer learning for colonic polyp classification; and deep learning algorithm for brain-computer interface. Section 4 focuses on deep learning applications in pattern recognition systems, describing application of deep learning in airport visibility forecast; hierarchical representations feature deep learning for face recognition; review of research on text sentiment analysis based on deep learning; classifying hand written digits with deep learning; and bitcoin price prediction based on deep learning methods.
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