Project centers in Chennai

IEEE Final Year Project Topic for CSE

Base Paper Title

Fast Supervised Discrete Hashing

Our Title

IEEE Project Abstract

Learning-based hashing algorithms are “hot topics” because they can greatly increase the scale at which existing methods operate. In this paper, we propose a new learning-based hashing method called “fast supervised discrete hashing” (FSDH) based on “supervised discrete hashing” (SDH). Regressing the training examples (or hash code) to the corresponding class labels is widely used in ordinary least squares regression. Rather than adopting this method, FSDH uses a very simple yet effective regression of the class labels of training examples to the corresponding hash code to accelerate the algorithm. To the best of our knowledge, this strategy has not previously been used for hashing. Traditional SDH decomposes the optimization into three sub-problems, with the most critical sub-problem - discrete optimization for binary hash codes - solved using iterative discrete cyclic coordinate descent (DCC), which is time-consuming. However, FSDH has a closed-form solution and only requires a single rather than iterative hash code-solving step, which is highly efficient. Furthermore, FSDH is usually faster than SDH for solving the projection matrix for least squares regression, making FSDH generally faster than SDH. For example, our results show that FSDH is about 12-times faster than SDH when the number of hashing bits is 128 on the CIFAR-10 data base, and FSDH is about 151-times faster than FastHash when the number of hashing bits is 64 on the MNIST data-base. Our experimental results show that FSDH is not only fast, but also outperforms other comparative methods.

Existing System

Drawback of Existing System

Proposed System

Advantage of Proposed System

Enhancement from Base Paper

Architecture

Technology Used : Hardware & Software

Existing Algorithm

Proposed Algorithm

Advantages of Proposed Algorithm

Project Modules

Literature Survey

Conclusion

Future Work

To View the Abstract Contents

Exclusive
Offer
Refer Your Friend
10%
CASHBACK
Refer Another Friend
Thanks for Referring Your Friend / Relation

Now it is Your Time to Shine.

Great careers Start Here.

We Guide you to Every Step

Success! You're Awesome

Thank you for filling out your information!

We’ve sent you an email with your Final Year Project PPT file download link at the email address you provided. Please enjoy, and let us know if there’s anything else we can help you with.

To know more details Call 900 31 31 555

The WISEN Team