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BME228
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BME228
index
CE
CE
ch00 : Introduction
ch00 : Introduction
What is a Computer?
History of Computer
컴퓨터 분류.
Computer 주요 구성 요소
ch01: Representation of Data
ch01: Representation of Data
Representation of data within a computer system.
Information (정보)
Bits and Boolean Algebra
Bits and Boolean Algebra
Bit (Binary Digit)
MSB and LSB
bit 관련 단위.
Boolean Algebra
Prefixs for SI Units and for bits (IEC)
Bits and Number
Bits and Number
Numeral System
양의 정수 표현하기
Negative Number
Overflow and Underflow
Real Number
Code for Number (Symbol)
Bits and Character
Bits and Character
Codes for Characters
Encodings
ch02: Bits and Combinatorial Logic
ch02: Bits and Combinatorial Logic
Building Hardware for Bits
Building Hardware for Bits
Building Hardware for Bits
relay
vacuum tube
transistor
IC
Gates
Gates
Gate에 대해서
Noise와 싸우기
Propagation Delay
Gate Outputs
Totem-pole Output
Open-Collector Output
Tri-State Output
Adder, Encoder, and Mux
Adder, Encoder, and Mux
Gate들을 이용한 보다 복잡한 회로들.
Adder
ch03: Sequential Logic and Memory
ch03: Sequential Logic and Memory
time and memory
time and memory
time and memory
oscillator
latch
flip-flop
counter
register
HW vs SW
ch04: Computer Structure
ch04: Computer Structure
Computer Structure
Memory (and Storage)
Memory (and Storage)
memory summary
RAM and ROM
RAM and ROM
memory 기초
RAM
ECC Memory
ROM
Block Device
Flash Memory
Address and Memory
Byte Ordering : Little Endian and Big Endian
I/O Device and Bus
I/O Device and Bus
Bus
I/O Device
CPU
CPU
The Central Processing Unit (CPU)
Arithmetic and Logic Unit, Shifter, and Control Unit
Instruction Sets
명령어 수행: Fetch and Execute
Signal Traffic Control
RISC vs. CISC
Parallel Computing
Parallel Computing
Parallel Computing
Graphics Processing Units
Cluster System
Grid Computing System
Multi-processor System
GPGPU System
병렬 컴퓨팅을 위한 주요 프로그래밍 모델과 프레임워크
ch05: Computer Architecture
ch05: Computer Architecture
Computer Architecture
Function in the Programming
Recursive Call and Data Structures
Interrupt and Polling
Relative Addressing : (OS, Index Register, Relative Addressing)
Memory Management Units (MMU)
Virtual Memory
ch06: Data Transfer and Network Communication
ch06: Data Transfer and Network Communication
Data Transfer
Data Transfer
IO Ports
Push Btns
FND
IO Mux
Duty Cycle
Gray Code
Parallel Transfer
Serial Transfer
USB
Network and Communication
Network and Communication
The History of Data Communication Network
Ethernet, Router, Switch and so on
Internet and Related Protocols
ch08 Programming Language and Language Processing
ch08 Programming Language and Language Processing
Programming Language
Low level language vs. High level language
Compiler Language and Interpreter Language
Machine Code
Assembly Language (어셈블리어)
High Level Programming Language
ch09
ch09
Web Browser
ch10
ch10
Concepts for Programming
Concepts for Programming
Command Line Interface
Standard I/O Library
작성중
작성중
Portability (이식성)
Package Management : apt, yum, brew 등등
Container and Virtual Machine
OS
OS
Operating System
Operating System (운영체제)
Kernel
Console, Terminal, and Shell
UNIX
LINUX
Windows OS
File, Folder, Directory and Commands for Console
File
Folder and Directory
Path (경로)
File System
Disk, Partition, and Volume
명령어 (Linux)
명령어 (Windows)
markdown and LaTeX
markdown and LaTeX
Markdown
LaTeX
OOP
OOP
OOP and Programming Paradigm
OOP and Programming Paradigm
Object Oriented Programming (OOP)
Object (객체) 란
Programming Paradigm
OOP vs. Structured Programming
참고: Declarative Programming Language vs. Imperative Programming Language
OOP Details
OOP Details
OOP 와 관련 개념들.
Abstraction (추상화) : Class and Instance
Encapsulation (and Data Hiding)
Modularity
Inheritance (상속)
OOP : Is-a and Has-a Relationship
Message Passing
Polymorphism (다형성)
OOP Etc
OOP Etc
Setter and Getter
OOP Summary
python
python
Python의 Class (차이점)
Python의 Encapsulation
Python
Python
Modules and Packages
DIP
DIP
OpenCV
OpenCV
Gui Features in OpenCV
Gui Features in OpenCV
1. OpenCV를 통한 Image 다루기 (읽고 쓰기)
Note: color space
2. Drawing Functions in OpenCV
Mouse as a Paint-Brush
Trackbar as the Color Palette
Core Operations
Core Operations
Basic Operations on Images
OpenCV에서 Padding
Arithmetic Operations on Images
Image Blending (or alpha Blending)
Image Processing
Image Processing
Color Space (Simple Version)
Histogram
Histogram-based Image Processing Techniques
Histogram Backprojection
Image Thresholding
Canny Edge Detection
Image Pyramid and Scale Space
Contour
Contour Features
Contour Properties
Low Pass Filter
High Pass Filter and Edge Detection
Laplacian of Gaussian (LoG)
Geometric Transformations of Images
Morphological Operations
Hough Transform
Circle Hough Transform
Template Matching : cv2.matchTemplate
etc
etc
cv2.floodfill
Convolution
Metrics for Image Quality
Image Feature
Image Feature
Local Image Features (or patch feature, local feature, feature)
Keypoint (특징점)
Keypoint Detection
Old Style Features
Old Style Features
Canny Edge Detection
Harris and Stephen Corner Detection (1988)
HOG (Histogram of Oriented Gradients)
ML
ML
Introduction
Introduction
Introduction
참고자료 : AI의 시작 ...
Machine Learning (ML)이란?
ML이 유용한 경우.
Categories of ML
Supervised Learning
Unsupervised Learning
Semi-supervised Learning
Self-supervised Learning
Reinforcement Learning (강화학습)
관련 용어들
Instance based Learning
Model based Learning
Model이란?
Online Learning
Batch Learning
ML의 주요 단계와 성공을 위해 고려해야하는 요소
Ex : End_to_End Learning
Ex : End_to_End Learning
[ML] Classic Regressor (Summary)
`train_test_split` 사용하기.
Cross Validation
Classification
Classification
Types of Classification
Performance Measures for Classifiers
Linear Regression and Logistic Regression
Linear Regression and Logistic Regression
Logistic Regression
Ensemble Learning
Ensemble Learning
Ensemble
Stacking
Dimensionality Reduction
Dimensionality Reduction
Principal Component Analysis
Multi-Dimensional Scaling (MDS)
Unsupervised Learning
Unsupervised Learning
Clustering (군집)
Manifold and Manifold Learning
Topological Space (위상공간)
t-distributed Stochastic Neighbor Embedding (t-SNE)
Deep Learning (simple)
Deep Learning (simple)
초창기 Artificial Neural Network
Back propagation (역전파, 오차 역전파)
Reverse-Mode Autodiff (Auto-Differentiation)
Graph
Solutions for the Gradient Vanishing or Exploding Problem
Weight Initialization (가중치 초기화)
Rectified Linear Unit (ReLU)
Exponential Linear Unit (ELU)
Sigmoid Linear Unit (SiLU) : from GELU to MiSH
Batch Normalization
Optimizers
Optimizers
Optimizers
Momentum
Nesterov Accelerated Gradient
Adaptive Gradient (AdaGrad)
Root Mean Square Propagation (RMSProp)
Adaptive Momentum Estimation (Adam)
Nesterove-accelerated Adaptive Momentum Adam (NADAM)
Transfer Learning
Transfer Learning
Transfer Learning
Hyperparameter Tuning
Hyperparameter Tuning
Keras Tuner
Hyper-Parameters in DL
CNN
CNN
Convolutional Neural Network, CNN
Convolutional Layer
Pooling Layer
LeNet-5
AlexNet
VGGNet
ResNet: Deep Residual Learning for Image Recognition (2015)
RNN
RNN
Recurrent Neural Network (순환신경망, `RNN`)
Memory Cell (or Cell)
Recurrent Neural Network Topologies (or The Types of RNN)
Bahdanau Attention
Attention Score (or Alignment)
GAN
GAN
Generative Adversarial Network (GAN)
Colab
Colab
Colab이란
Colab의 구성
Colab : Hotkeys
Colab: GPU 사용하기
SS
SS
z-Transform
z-Transform
Time Shift : Properties of z-Transform
Material Test
Material Test
code blk
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