| dc.description.abstract | The advancement of developed countries in the twentieth century is measured by
software development. Artificial Intelligence (AI) and its various sub-domains are
progressively being used to assist in recurring processes in numerous industries and businesses.
AI has played a significant role in improving the way we amuse ourselves, engage with our
mobile devices, and even drive our vehicles. We are more likely than not exposed to Machine
Learning (ML) algorithms and Natural Language Processing (NLP) in a variety of everyday
tasks. Artificial intelligence (AI) and machine learning (ML)-powered software and devices are
imitating human thought patterns to aid society's digital transformation. AI systems interpret
their surroundings, respond to what they see, solve problems, and assist with tasks to make life
easier.
Fish species identification is a challenge for people all over the world, and they require
access to scientific knowledge in order to do so. An automated method of identifying fish
species would be extremely useful. As a result, in this thesis, an inventive smartphone
application for identifying common fish species has been developed. The primary purpose of
this thesis is to develop a mobile application that assists consumers in distinguishing between
fish species. This study methodology was created using Image Processing and Artificial
Intelligence, the research culminates in a fish classification mobile application that achieves the
primary goal mentioned earlier. Regardless, this mobile application has the potential to be a
massive database of all aquatic species and types of fish. Trained models can achieve 98% of
accuracy in the predictions. | en_US |
