Purpose: Communication is the passport of success. The objective this undertaking was to fabricate a neural network ready group which letter American Sign Language (ASL) letters in order being marked, given picture marking hand. Design/Methodology/Approach: It developed using Python programming with help TensorFlow for all AI-related tasks and Deep Learning. Findings/Result: This examination an...

Deafness does not restrict its negative effect on the person’s hearing, but rather all aspect of their daily life. Moreover, hearing people aggravated issue through reluctance to learn sign language. This resulted in a constant need for human translators assist deaf person which represents real obstacle social Therefore, automatic language translation emerged as an urgent community. The availab...

Bangladeshi Sign Language (BdSL) is a commonly used medium of communication for the hearing-impaired people in Bangladesh. A real-time BdSL interpreter with no controlled lab environment has broad social impact and an interesting avenue research as well. Also, it challenging task due to variation different subjects (age, gender, color, etc.), complex features, similarities signs clustered backg...

Traffic Sign Recognition (TSR) is one of the most sought-after topics in computer vision, mostly due to increasing scope and advancements self-driving cars. In our study, we attempt implement a TSR system that helps driver stay alert during driving by providing information about various traffic signs encountered. We will be looking at working model classifies gives output form an audio message....

This paper introduces the end-to-end embedding of a CNN into a HMM, while interpreting the outputs of the CNN in a Bayesian fashion. The hybrid CNN-HMM combines strong discriminative abilities of CNNs with sequence modeling capabilities of HMMs. Most current approaches in the field of gesture and sign language recognition disregard the necessity of dealing with sequence data both for training a...