Published Paper Details:

E-commerce websites are becoming extremely prevalent, with a significant volume of individuals embracing this medium. This seems to be due to the enhanced accessibility and simplicity of use that these networks provide when it start shopping for necessities as well as other things from the convenience of your own home. This has enabled many handicapped people and others with accessibility concerns to successfully remain at home and purchase different products that they require. This has resulted in a plethora of e-commerce companies fighting for consumers' focus and attempting to grow their customer base in order to deliver accurate alternatives with simplicity. The integration of speech and gesture-based searching for items on e-commerce platforms is one example of something like this. The paradigm of utilizing Convolution Neural Network for the recognition of the gestures is one of the most difficult approaches that require extensive computations along with the region of interest estimation. The obtained results are indicate better performance of the system through the use of Root mean square Error evaluation.