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Because of the world’s current affinity towards data-driven industries, machine learning has become an exceedingly popular area of study and research in recent years, especially in regards to image processing and recognition. The most common learning tools in image recognition are neural networks, which consist of a series of connected layers of “neurons”.

In a standard neural network, each layer takes an input vector, every element of which is connected to each neuron in the layer with a specific “weight”. Moreover, each neuron in a layer has a specific “bias” associated with it, designed so that the neuron will only produce a meaningful output if the linear combination of weighted inputs (the neuron’s excitation) is greater than that bias. This output is determined by passing the neuron’s net excitation to an activation function. With the inputs propagating through each layer of the network in this fashion, the neural network produces an output corresponding to both an input and the parameters (weights and biases) of the network. The network then learns through a Stochastic Gradient Descent algorithm, which updates all of the network’s parameters in attempts to minimize a cost function that defines the relationship between a network’s produced output and a desired output. This entire training process is repeated for a specified number of epochs to improve accuracy.

A convolutional neural network (CNN) is similar to a standard neural network except it adds convolutional layers at the beginning. Convolutional layers arrange neurons into grids, and convolve those grids with input images. The parameters of the convolutional layers are the weights of each neuron in each filter’s kernel and the bias applied to each filter. The output of the convolutional layers is then passed to the fully connected layers of a standard neural network.

Our project focused on applying convolutional neural networks to handwritten digits, allowing us to build a system that was able to recognize the digits 0-9 with a great deal of accuracy. Because of the simplicity of this problem, we were better able to understand the structure of the tool used to solve the problem. With this deeper understanding of convolutional neural networks, we are better equipped to solve more complex problems.

Project motivation

Because machine learning has become such a significant area of study and research, we were interested in pursuing a project that would give us an introduction to the concept. This, and because of our collective interest in image recognition, is why we chose to explore convolutional neural networks. We chose handwritten digits as our dataset because it was a set readily available to us, and because it was a simple enough problem where we could focus our efforts on understanding the learning process, network structure, and functionality of each layer rather than having to waste effort delving into the nuances of a complicated dataset, such as facial or animal recognition.

Previous work

Convolutional neural networks are an extremely saturated field, with many papers and studies done on them. Many different methods for improving their performance have been explored by researchers; such as independently training a set of networks and having them vote on the most likely output. We used the results of all of this research to formulate a structure for our network and to postulate new methods for improving performance, such as knowledge transfer between networks.

Questions & Answers

Is there any normative that regulates the use of silver nanoparticles?
Damian Reply
what king of growth are you checking .?
What fields keep nano created devices from performing or assimulating ? Magnetic fields ? Are do they assimilate ?
Stoney Reply
why we need to study biomolecules, molecular biology in nanotechnology?
Adin Reply
yes I'm doing my masters in nanotechnology, we are being studying all these domains as well..
what school?
biomolecules are e building blocks of every organics and inorganic materials.
anyone know any internet site where one can find nanotechnology papers?
Damian Reply
sciencedirect big data base
Introduction about quantum dots in nanotechnology
Praveena Reply
what does nano mean?
Anassong Reply
nano basically means 10^(-9). nanometer is a unit to measure length.
do you think it's worthwhile in the long term to study the effects and possibilities of nanotechnology on viral treatment?
Damian Reply
absolutely yes
how to know photocatalytic properties of tio2 nanoparticles...what to do now
Akash Reply
it is a goid question and i want to know the answer as well
characteristics of micro business
for teaching engĺish at school how nano technology help us
Do somebody tell me a best nano engineering book for beginners?
s. Reply
there is no specific books for beginners but there is book called principle of nanotechnology
what is fullerene does it is used to make bukky balls
Devang Reply
are you nano engineer ?
fullerene is a bucky ball aka Carbon 60 molecule. It was name by the architect Fuller. He design the geodesic dome. it resembles a soccer ball.
what is the actual application of fullerenes nowadays?
That is a great question Damian. best way to answer that question is to Google it. there are hundreds of applications for buck minister fullerenes, from medical to aerospace. you can also find plenty of research papers that will give you great detail on the potential applications of fullerenes.
what is the Synthesis, properties,and applications of carbon nano chemistry
Abhijith Reply
Mostly, they use nano carbon for electronics and for materials to be strengthened.
is Bucky paper clear?
carbon nanotubes has various application in fuel cells membrane, current research on cancer drug,and in electronics MEMS and NEMS etc
so some one know about replacing silicon atom with phosphorous in semiconductors device?
s. Reply
Yeah, it is a pain to say the least. You basically have to heat the substarte up to around 1000 degrees celcius then pass phosphene gas over top of it, which is explosive and toxic by the way, under very low pressure.
Do you know which machine is used to that process?
how to fabricate graphene ink ?
for screen printed electrodes ?
What is lattice structure?
s. Reply
of graphene you mean?
or in general
in general
Graphene has a hexagonal structure
On having this app for quite a bit time, Haven't realised there's a chat room in it.
what is biological synthesis of nanoparticles
Sanket Reply
how did you get the value of 2000N.What calculations are needed to arrive at it
Smarajit Reply
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Source:  OpenStax, Handwritten digit recognition using convolutional neural networks. OpenStax CNX. Dec 15, 2015 Download for free at http://legacy.cnx.org/content/col11922/1.6
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