TY  - BOOK
AU  - ONIMSI, ThankGod Ayomide
TI  - AVO and Seismic Attributes Analysis of OTG Field, Deep Offshore Niger Delta
PY  - 2020///
CY  - Ibafo
PB  - Geosciences
KW  - Geophysics
N2  - Classification and identification of images from images from objects using machine learning.
In our world today, object classification and identification helps detect and define objects such
as humans, buildings and cars from digital images, it is a computer technology related computer
vision and image processing. The aim was to identify and classify objects using convolutional
neural network and the objectives; to formulate an algorithm, develop a model and evaluate
the model. This project work presents the building process of a model to identify and classify
object images from different objects. This chapter reports the design phase of the model, it
involves decomposing the whole system into smaller parts and defining the relationship among
the constituent parts.
Top down design approach was employed in design and development phases of this project
work. This involved dividing the system into subsystems or modules and each subsystem being
further divided into even smaller subs. This process of division is repeated until each module
is sufficiently small enough to be conveniently coded (implemented) from scratch as an
independent entity that performs a clearly defined operation. At the beginning of the project,
the tools to be used for this project were downloaded, the tools used for the project were the
Kaggle Dataset API, Google Chrome, A Kaggle JSON file.
One of the libraries used was matplotlib. Matplotlib is a Python 2D plotting library which
produces publication quality figures in a variety of hardcopy formats and interactive
environments across platforms. Matplotlib can be used in Python scripts, the Python
and IPython shells, the Jupyter notebook, web application servers, and four graphical user
interface toolkits.
Classification and identification of images from images from objects using machine learning.
In out world today,object classification and identification helps detect and define objects such
as humans, buildings and cars from digital images, it is a computer technology related computer
vision and image processing. The aim was to identify and classify objects using convolutional
neural network and the objectives;to formulate an algorithm,develop a model and evaluate the
model. This project work presents the building process of a model to identify and classify
object images from different objects. This chapter reports the design phase of the model, it
involves decomposing the whole system into smaller parts and defining the relationship among
the constituent parts.
vi
Top down design approach was employed in design and development phases of this project
work. This involved dividing the system into subsystems or modules and each subsystem being
further divided into even smaller subs. This process of division is repeated until each module
is sufficiently small enough to be conveniently coded (implemented) from scratch as an
independent entity that performs a clearly defined operation. At the beginning of the project,
the tools to be used for this project were downloaded, the tools used for the project were the
Kaggle Dataset API, Google Chrome, A Kaggle JSON file.
One of the libraries used was matplotlib. Matplotlib is a Python 2D plotting library which
produces publication quality figures in a variety of hardcopy formats and interactive
environments across platforms. Matplotlib can be used in Python scripts, the Python
and IPython shells, the Jupyter notebook, web application servers, and four graphical user
interface toolkits.
All this methods and materials were deployed for this project and object classification and
identification such as humans,cars,buildings was successful
ER  -