Web application

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.