Titlebook: Enabling AI Applications in Data Science; Aboul-Ella Hassanien,Mohamed Hamed N. Taha,Nour El Book 2021 The Editor(s) (if applicable) and T

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https://doi.org/10.1007/3-540-27986-5ying diseases. This chapter introduces a survey on research papers on leaf plant diseases detection based on DL, and analyze in terms of the database used, transfer models, and miss-classification achieved.

BRIEF

Hysteresis, entrapment, and contact angle size for classification and detection of medical diagnoses are explained. Moreover, specific methods are considered in medical images such as image compression, image format, image resize, and other essential aspects. Finally, we also give a brief summary of deep learning algorithms that are used with medical images.

荒唐

Pericarditis

Towards Artificial Intelligence: Concepts, Applications, and Innovationsion of their projects. The contributions presented in this document reveal the high potential of AI methods as tools for predicting and optimizing different applications. In addition, challenges and directions for future research in the area of the use of AI techniques are presented and discussed.

公司

Big Data and Deep Learning in Plant Leaf Diseases Classification for Agricultureying diseases. This chapter introduces a survey on research papers on leaf plant diseases detection based on DL, and analyze in terms of the database used, transfer models, and miss-classification achieved.

keloid

Machine Learning Cancer Diagnosis Based on Medical Image Size and Modalities size for classification and detection of medical diagnoses are explained. Moreover, specific methods are considered in medical images such as image compression, image format, image resize, and other essential aspects. Finally, we also give a brief summary of deep learning algorithms that are used with medical images.

莎草

催眠药

Stochastic SPG with Minibatchesnificantly onto proximal gradient iterations, in order to find an efficient approach for nonsmooth (composite) population risk functions. The complexity of finding optimal predictors by minimizing regularized risk is largely understood for simple regularizations such as . norms. However, more comple

ANTIC

Commonplace

Reducing Redundant Association Rules Using Type-2 Fuzzy Logicificial intelligence, machine learning, and soft computing. Association Rule Mining (ARM) in enormous databases is a fundamental topic of DM. Discovering frequent itemsets are an underlying process in ARM. Frequent itemsets are employed using statistical measures like Support (Sup) and Confidence (C