Sign Explainer An Explainable AI Enabled Framework for Sign Language Recognition With Ensemble Learning

Sign Explainer An Explainable AI Enabled Framework for Sign Language Recognition With Ensemble Learning

₹5,500.00
Product Code: Matlab - Deep Learning
Availability: In Stock
Viewed 2283 times

Product Description

Aim:

         To enhance the accuracy, robustness and interpretability of sign language recognition system

Synopsis:

         Sign Language recognition is a pioneering framework designed to advance the field of Sign Language Recognition (SLR) through the innovative application of Ensemble Deep learning models. The primary goal of this research is to significantly improve the accuracy, resilience and interpretability of SLR systems. Leveraging the unique features of ResNet within an ensemble learning paradigm. The key component of InceptionResNetv2 architecture is its deep and effective feature extraction capabilities. The utilization of Inception ResNet model enhances the model ability to capture intricate details crucial for accurate sign language recognition. This framework is also to scale seamlessly, accommodating an expanding vocabulary of signs, diverse users and dynamic environmental conditions without compromising performance

Proposed System:

          Sign language recognition is a critical aspects of facilitating communication for the deaf and hard-of-hearing community. This research introduces an innovative approach utilizing the inceptionResNetV2 architecture for robust and accurate sign language classification. A diverse dataset is employed, encompassing a variety of sign language gestures captured from real world scenarios. The proposed methodology involves the transfer learning technique, adapting the InceptionResNetV2 model to the specific requirements of sign language recognition. The model is fine-tuned with a new classification layer to suit the unique characteristic of the dataset. Additionally, data augmentation techniques are applied to enhance the models generalization capability. Training and Validation are conducted on a carefully partitioned dataset and the performance is evaluated through a comprehensive set of metrics. The resulting model demonstrates high accuracy, showcasing its potential for practical applications in real time sign language recognition scenarios. The study contributes to the ongoing efforts in developing efficient human-machine communication system for the deaf and hard of hearing community. The InceptionResNetV2 based model offers promising results, emphasizing its efficiency in advancing the state of the art in sign language recognition technology.


When you order from finalyearprojects.in, you will receive a confirmation email. Once your order is shipped, you will be emailed the tracking information for your order's shipment. You can choose your preferred shipping method on the Order Information page during the checkout process.

The total time it takes to receive your order is shown below:

The total delivery time is calculated from the time your order is placed until the time it is delivered to you. Total delivery time is broken down into processing time and shipping time.

Processing time: The time it takes to prepare your item(s) to ship from our warehouse. This includes preparing your items, performing quality checks, and packing for shipment.

Shipping time: The time for your item(s) to tarvel from our warehouse to your destination.

Shipping from your local warehouse is significantly faster. Some charges may apply.

In addition, the transit time depends on where you're located and where your package comes from. If you want to know more information, please contact the customer service. We will settle your problem as soon as possible. Enjoy shopping!

Download Abstract

Click the below button to download the abstract.

Package Includes

Software Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support


The Delivery time for software projects is 2 -3 working days. Some of the software projects will require Hardware interface. Please go through the hardware Requirements in the abstract carefully. The Hardware will take 7-8 Working Days

 

Hardware Projects Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. Datasheets
  6. Circuit Diagrams
  7. Source Code
  8. Screen Shots & Photos
  9. Software Links
  10. Reference Papers
  11. Lit survey
  12. Full Project Documentation
  13. Online support


The Delivery time for Hardware projects is 7-8 working days.

   

Mini Projects: Software Includes

  1. Demo  Video
  2. Abstract
  3. Base paper
  4. Full Project PPT
  5. UML Diagrams
  6. SRS
  7. Source Code
  8. Screen Shots
  9. Software Links
  10. Reference Papers
  11. Full Project Documentation
  12. Online support

 

The Delivery time for software Miniprojects is 2 -3 working days.

 

Mini Projects - Hardware includes

  1. Demo  Video
  2. Abstract
  3. PPT
  4. Datasheets
  5. Circuit Diagrams
  6. Source Code
  7. Screen Shots & Photos
  8. Software Links
  9. Reference Papers
  10. Full Project Documentation
  11. Online support

The Delivery time for Hardware Mini projects is 7-8 working days.