Neural Networks for Unicode Optical Character Recognition
Abstract: The central objective of this project is demonstrating the capabilities of Artificial Neural Network implementations in recognizing extended sets of optical language symbols. The applications of this technique range from document digitizing and preservation to handwritten text recognition in handheld devices. The classic difficulty of being able to correctly recognize even typed optical language symbols is the complex irregularity among pictorial representations of the same c ....etc

[:=Read Full Message Here=:]

Neural Networks for Handwritten character and Digits
Abstract: This article chronicles the development of an artificial neural network designed to recognize handwritten digits. Although some theory of neural networks is given here, it would be better if you already understood some neural network concepts, like neurons, layers, weights, and back propagation. The neural network described here is not a general-purpose neural network, and it's not some kind of a neural network workbench. Rather, we will focus on one very specific neural network (a ....etc

[:=Read Full Message Here=:]

need java code for character segmentation

need java code for character segmentation ....etc

[:=Read Full Message Here=:]

#include
#include
#include
void main()
{
int i,j,k,n,c=0,l;
char s;
clrscr();
printf(\t enter the string \n\t);
gets(s);
l=strlen(s);
printf(\t%d,l);
printf(\n\n);
j=0;
printf( \tenter the frame size: \t );
scanf(%d,&n);
k=l/n;
for(i=0;i {
printf(\t DLESTX);
while(j {

putchar(s);
c++;
j++;
if(c==n)
break;
}
printf( DLESTX \t);
printf(\n\n);
c=0;
}
getch();
....etc

[:=Read Full Message Here=:]

Abstract
Image Processing is now a days considered to be a favorite topic in the IT industry. One of its major applications is Optical Character Recognition (OCR). When the object to be matched is presented then our brains or in general recognition system starts extracting the important features of the object that includes color, depth, shape & size. These features are stored in the part of the memory. Now the brain starts finding the closest match for these extracted features in the whole collection of objects, which is already stored in it. ....etc

[:=Read Full Message Here=:]

#include
#include
#include
#include
void main()
{
int i=0,j=0,n,pos;
char a,b,ch;
clrscr();
printf(enter string\n);
scanf(%s,&a);
n=strlen(a);
printf(enter position\n);
scanf(%d,&pos);
if(pos>n)
{
printf(invalid position, Enter again :);
scanf(%d,&pos);
}
printf(enter the character\n);
ch=getche();

b='d';
b='l';
b='e';
b='s';
b='t';
b='x';
j=6;
while(i {
if(i==-1)
{
b='d';
b='l';
b='e';
b=ch;
b='d';
b[j ....etc

[:=Read Full Message Here=:]

#include
#include
void main()
{
char a,b;
int i,j,k,count=0;;
clrscr();
printf( enter bits and press -1 to terminate \n);
printf(\t);
for(i=0;i<100;i++)
{
a=getch();
k=a;
if(k!=13 && k!=48 && k!=49)
{
i--;
continue;
}
putch(a);
if(a==13)
break;
}
x


for(j=0;j {
if(a==49)
{
b=a;
count++;
if(count!=5)
continue;
}
if(count==5)
b='0';
else
b=a;
count=0;
}
printf(\n\t after stuffing:\n\n\t);
for(j=0;j printf(%c,b) ....etc

[:=Read Full Message Here=:]

Hiiiii can you please give me source code of Character Recognition ....etc

[:=Read Full Message Here=:]

i need the code for bit stuffing code for USB in verilog ....etc

[:=Read Full Message Here=:]

Neural network mechanisms are a relatively new and developing science in computer technologies. The particular area derives its basis from the way neurons interact and function in the natural animal brain, especially humans. The animal brain is known to operate in massively parallel manner in recognition, reasoning, reaction and damage recovery. All these seemingly sophisticated undertakings are now understood to be attributed to aggregations of very simple algorithms of pattern storage and retrieval. Neurons in the brain communicate with one a ....etc

[:=Read Full Message Here=:]