PPT on Object Recognition

2. Project Overview
 Object Recogition is the technology in the field of computer vision for finding
and identifying objects in an image or video.
 Humans recognize a multitude of objects in images with little effort, despite
the fact that the image of the objects may vary somewhat in different
viewpoints, in many different sizes and scales or even when they are
translated or rotated.
 Objects can even be recognized when they are partially obstructed from
view. This task is still a challenge for computer vision systems. Many
approaches to the task have been implemented over multiple decades.

3. Android Studio is the new integrated
development environment (IDE) fast
replacing Eclipse. Android Studio is
based on the IntelliJ IDEA
Community Edition, a Java IDE by
Jet Brains, for developing for the
Android mobile platform. It provides
access to the Android developers'
tools for development & debugging,
helping you to design, test and
monetize your Android apps. It was
introduced at the Google I/O 2013
conference; the stable build (v1.0)
being released in December 2014.
Android Studio 1.1 is now available
for download on various OS like
Windows, Mac, OS X and Linux.

4. Android Studio improves on Eclipse IDE with numerous new features. In
the long run, Google aims to replace Eclipse with Android Studio as the
primary IDE for developing Android apps. Let’s discover the features of
this new IDE!

5.  Java Language
 Machine Learning
 Tensorflow
 Keras
 Kaggle

6.  Java is a general-purpose computer-programming
language that is concurrent, class-based, object-oriented
and specifically designed to have as few implementation
dependencies as possible.
 In Android studio, we can make projects with either Java
language or Kotilin but I have used Java language in my
project because it is more simpler to understand.

7.  Machine Learning is a subset of artificial intelligence which
focuses mainly on machine learning from their experience and
making predictions based on its experience.
 It enables the computers or the machines to make data-driven
decisions rather than being explicitly programmed for carrying
out a certain task. These programs or algorithms are designed
in a way that they learn and improve over time when are
exposed to new data.
 Machine Learning algorithm is trained using a training data set
to create a model. When new input data is introduced to the
ML algorithm, it makes a prediction on the basis of the model.

8. Types of Machine Learning
Machine learning is sub-categorized to three types:
•Supervised Learning
•Unsupervised Learning
•Reinforcement Learning

9.  TensorFlow is the most famous deep learning library
these recent years. A practitioner using TensorFlow can
build any deep learning structure, like CNN, RNN or
simple artificial neural network.
 Google wants to use machine learning to take advantage
of their massive datasets to give users the best
experience. Three different groups use machine learning:
1.Researchers
2.Data scientists
3.Programmers.

10.  TensorFlow is the best library of all because it is built to
be accessible for everyone.
 Tensorflow library incorporates different API to built at
scale deep learning architecture like CNN or RNN.
 TensorFlow is based on graph computation; it allows the
developer to visualize the construction of the neural
network with Tensorboad.
 This tool is helpful to debug the program. Finally,
Tensorflow is built to be deployed at scale. It runs on
CPU and GPU.

11. Keras is a high-level neural networks API,
written in Python and capable of running
on top of TensorFlow, CNTK, or Theano.
It was developed with a focus on enabling
fast experimentation.
Being able to go from idea to result with
the least possible delay is key to doing
good research.