Published: July 9, 2024
Language: Английский
Published: July 9, 2024
Language: Английский
Computational Biology and Bioinformatics, Journal Year: 2023, Volume and Issue: unknown
Published: Dec. 5, 2023
Managing fisheries requires regular monitoring and assessment of fish populations.Traditional methods evaluating stocks, particularly their size, can be time-consuming, labor-intensive, inaccurate.Recently, digital image processing (DIP) machine learning (ML) have emerged as promising technologies to automate measurement classification.In this study, we aim develop deep models predict, classify shape size the using convolutional neural networks (CNNs) DIP techniques.The study utilizes publicly available datasets evaluates efficiency proposed metrics such precision, recall, F1 score.The developed utilize Python programming language with TensorFlow Keras libraries.The regression component investigates intricate relationship between various physical attributes fish, uncovering connections body length, height, weight.This analysis provides valuable insights into correlations among these attributes, enhancing our understanding characteristics.Simultaneously, classification segment introduces an innovative approach classification, incorporating attributes.Through a combination classifiers ensemble stacking, exceptional accuracy is achieved in identifying distinct classes.This integration techniques facilitates more nuanced process, allowing for comprehensive categorization based on visual attributes.Our establishes robust framework Utilizing combined strengths (ML).The not only enhance but also contribute broader goal sustainable management.This research sets foundation future endeavors automating stock assessments, contributing advancement science management practices.
Language: Английский
Citations
1Optical and Quantum Electronics, Journal Year: 2024, Volume and Issue: 56(4)
Published: Feb. 1, 2024
Language: Английский
Citations
0Campus, Journal Year: 2024, Volume and Issue: 29(37), P. 207 - 214
Published: June 26, 2024
Sistema basado en IoT y visión por computadora para monitoreo acuacultura
Citations
0Published: April 26, 2024
Language: Английский
Citations
0Published: July 9, 2024
Language: Английский
Citations
0