Database System Concepts and Architecture

Title: Elmasri_6e_Ch02.ppt Author: Raj Sunderraman Created Date: 8/23/2011 1:18:19 PM

Embedded SQL - tinman.cs.gsu.edu

3.4 Connecting to Oracle 99 Inthiscodefragment, aparticularzipcodevalueischeckedtoseeifitisalready present in the zipcodes table using the EXEC SQL select into statement.

  Oracle

The Enhanced Entity- Relationship (EER) Model

Generalization Hierarchies and Lattices (cont’d.) Multiple inheritance Subclass with more than one superclass If attribute (or relationship) originating in the same superclass inherited more than once via different paths in lattice • Included only once in shared subclass Single inheritance

  Inheritance, Hierarchies

ER & EER to Relational Mapping

relational database schema; the primary keys are underlined. DEPT_LOCATIONS. DNUMBER DLOCATION. Chapter 9 8. Step 7: For each . n-ary relationship type R, n>2 • Create a new relation S to represent R. • Include as foreign key attributes in the S the primary keys of the relations that represent

  Database, Relational, Relational database

ER & EER to Relational Mapping

relationship into a relational schema you must use one of the four options available. Let C be the super-class, K its primary key and A. 1, A. 2, …, A. n. its remaining attributes and let S. 1, S. 2, …, S. m. be the sub-classes. Chapter 9 11. Option 8A (multiple relation option):

  Relational, Schema, Relational schema

Convolutional Neural Networks (CNNs / ConvNets)

CS231n Convolutional Neural Networks for Visual Recognition. Recall: Regular Neural Nets. As we saw in the previous chapter, Neural Networks receive an input (a single vector), and transform it through a series of hidden layers. ... Convolutional Neural Networks take advantage of the fact that the input

  Network, Visual, Recognition, Neural network, Neural, Convolutional, Convolutional neural networks, Convolutional neural networks for visual recognition

Image Style Transfer Using Convolutional Neural Networks

datasets [6] and even to other visual information processing tasks [19, 4, 2, 9, 23], including texture recognition [5] and artistic style classification [15]. In this work we show how the generic feature represen-tations learned by high-performing Convolutional Neural Networks can be used to independently process and ma-

  Network, Styles, Visual, Transfer, Recognition, Neural, Convolutional, Convolutional neural networks, Style transfer

Convolutional Neural Networks for Visual Recognition

Convolutional Neural Networks for Visual Recognition A fundamental and general problem in Computer Vision, that has roots in Cognitive Science Biederman, Irving. "Recognition-by-components: a theory of human image understanding." Psychological review 94.2 (1987): 115.

  Network, Visual, Recognition, Neural, Convolutional, Convolutional neural networks for visual recognition

Large-scale Video Classification with Convolutional Neural ...

cently, Convolutional Neural Networks (CNNs) [15] have been demonstrated as an effective class of models for un-derstanding image content, giving state-of-the-art results on image recognition, segmentation, detection and retrieval [11,3,2,20,9,18]. The key enabling factors behind these results were techniques for scaling up the networks to tens

  Network, Large, Scale, Classification, Video, Recognition, Neural, Convolutional, Convolutional neural networks, Convolutional neural, Large scale video classification

3D Convolutional Neural Networks for Human Action …

3D Convolutional Neural Networks for Human Action Recognition (a) 2D convolution t e m p o r a l (b) 3D convolution Figure 1. Comparison of 2D (a) and 3D (b) convolutions. In (b) the size of the convolution kernel in the temporal dimension is 3, and the sets of connections are color-coded so that the shared weights are in the same color. In 3D

  Network, Recognition, Neural, Convolutional, Convolutional neural networks

Lecture 10: Recurrent Neural Networks

Ba, Mnih, and Kavukcuoglu, “Multiple Object Recognition with Visual Attention”, ICLR 2015. Gregor et al, “DRAW: A Recurrent Neural Network For Image Generation”, ICML 2015 Figure copyright Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, and Daan Wierstra, 2015. Reproduced with permission. Classify images by taking a

  Network, Visual, Recognition, Neural, Recurrent, Recurrent neural, Recurrent neural networks

ImageNet Classification with Deep Convolutional Neural ...

capacity. However, the immense complexity of the object recognition task means that this prob-lem cannot be specified even by a dataset as large as ImageNet, so our model should also have lots of prior knowledge to compensate for all the data we …

  Recognition, Neural, Convolutional, Convolutional neural