# Sign Language Detection

Source: [Sign Language Detection](<https://www.sota2.com/research/paper/68fa6d6a1e209131cea39ac1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:17:30.383Z

Authors: Shubham Deshmukh, Favin Fernandes, Amey Chavan

Published: 2022-09-08T06:05:28.000Z

## Abstract

With the advancements in Computer vision techniques the need to classify images based on its features have become a huge task and necessity. In this project we proposed 2 models i.e. feature extraction and classification using ORB and SVM and the second is using CNN architecture. The end result of the project is to understand the concept behind feature extraction and image classification. The trained CNN model will also be used to convert it to tflite format for Android Development.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2209.03578>)

[PDF](<https://arxiv.org/pdf/2209.03578.pdf>)