International Journal Of Imaging

Abstract

AI-Powered Automatic Fish Species Classification and Detection toward Smart Aquaculture

Author: Bhageerath Goud, Chaitanya yadav , Rajesh,N .Vishwanath

Abstract:

sharing to optimize computational cost. By using a single basic block for inference, the system enhances model efficiency while The classification of plant seedlings plays a crucial role in sustainable agriculture, with the global market for smart farming projected to reach $22 billion by 2025. Approximately 40% of agricultural produce is lost due to weeds and misidentification of plant species, highlighting the need for effective classification systems. Furthermore, inefficient manual identification methods can lead to reduced crop yields and increased costs for farmers. Existing systems predominantly rely on manual labor for seedling identification, which is time-consuming and prone to human error. This research proposes a novel deep learning framework that incorporates image data preprocessing techniques to enhance the accuracy of plant seedling classification. By leveraging convolutional neural networks (CNNs) and employing an ensemble classification approach, the proposed s