Abstract:
This paper explores fish identification for blind people utilizing multi-image
recognition including deep learning techniques. Our system was built using Speech
Recognition to support blind people in knowing about various fish in the market or
somewhere else. According to our preliminary study, the majority of blind people in
Bangladesh face difficulties purchasing various products, especially fish, from the
market. However, there is no automated device available that can identify the fish and
offer an interpretation. For this generosity of spirit, we created a system for visual
imperial people that will automatically identify and explain the fish using speech
recognition. We employed Deep Learning (DL) resources like Matploatlib,
TensorFlow, Keras, and others throughout the process. We utilized TensorFlow for
image preprocessing and classification. We used the most popular image processing
algorithm, Convolutional Neural Network (CNN), to evaluate the reliability of our
work. We tested three CNN models to see which one offered the best performance.
We compared all of the models before identifying multiple fishes with the model that
provided the highest precision and efficiency.
