Crab Age Prediction

Keywords: Crab, Age

Background

Crab age prediction plays a vital role in fisheries management and ecological research. Traditional methods for estimating crab age are often time-consuming and require destructive techniques. In this study, we propose a novel approach utilizing ANN for predicting the age of crabs based on various morphological features, including sex, length, diameter, height, weight, shucked weight, viscera weight, shell weight, and age. The study of the "Crab Age prediction" likely pertains to a predictive model or methodology aimed at estimating the age of crabs. This could involve analyzing various physiological, morphological, or behavioral traits to determine the age of crabs without resorting to time-consuming methods like examining growth rings. Such research would have implications for marine ecology, fisheries management, and conservation efforts by providing a more efficient way to estimate crab populations' age structures.

Aim & Objectives

Aim
To Predict the Crab Age Using DL Techniques
Objective
Develop an efficient and non-destructive method for predicting the age of crabs using artificial neural networks (ANN) based on a range of morphological features, contributing to improved fisheries management and ecological research

Research Methodology

ANN Technique used

Software & Tools

Jupyter, Google Collab

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