Image-based wheat mosaic virus detection with Mask-RCNN model

D Kumar, V Kukreja - … conference on decision aid sciences and …, 2022 - ieeexplore.ieee.org
Wheat is one of the most vital crops around the globe. Due to wheat mosaic virus disease,
there are a huge amount of yield quality losses. The mosaic virus is transmitted through curl …

[HTML][HTML] Charting the aquaculture internet of things impact: Key applications, challenges, and future trend

AF Abdullah, HC Man, A Mohammed, MM Abd Karim… - Aquaculture …, 2024 - Elsevier
Aquaculture plays a pivotal role in global food production, grappling with distinct hurdles in
water quality, feeding operation, and disease control. Efficient management of these core …

Water pollution reduction for sustainable urban development using machine learning techniques

I Priyadarshini, A Alkhayyat, AJ Obaid, R Sharma - Cities, 2022 - Elsevier
Water quality is affected by increased urbanization as pollutants produced in the urban
environment settle and contaminate water, and there is an increase in competition of water …

Automatic shrimp counting method using local images and lightweight YOLOv4

L Zhang, X Zhou, B Li, H Zhang, Q Duan - Biosystems Engineering, 2022 - Elsevier
Highlights•An automatic shrimp counting method is proposed.•A lightweight YOLOv4 model
is constructed.•The method reduces the time of image annotation in deep learning.•The …

Multi-classification deep neural networks for identification of fish species using camera captured images

H Malik, A Naeem, S Hassan, F Ali, RA Naqvi, DK Yon - Plos one, 2023 - journals.plos.org
Regular monitoring of the number of various fish species in a variety of habitats is essential
for marine conservation efforts and marine biology research. To address the shortcomings of …

HRFSVM: Identification of fish disease using hybrid Random Forest and Support Vector Machine

G Jhansi, K Sujatha - Environmental Monitoring and Assessment, 2023 - Springer
Aquaculture fish diseases pose a serious threat to the security of food supplies. Fish species
vary widely, and because they resemble one another so much, it is challenging to …

Underwater target detection algorithm based on improved YOLOv4 with SemiDSConv and FIoU loss function

C Zhang, G Zhang, H Li, H Liu, J Tan… - Frontiers in Marine …, 2023 - frontiersin.org
Underwater target detection is an indispensable part of marine environmental engineering
and a fast and accurate method of detecting underwater targets is essential. Although many …

SLCOBNet: Shrimp larvae counting network with overlap** splitting and Bayesian-DM-count loss

Y Qu, S Jiang, D Li, P Zhong, Z Shen - Biosystems Engineering, 2024 - Elsevier
Estimating the number of shrimp larvae plays a critical role for achieving reasonable feeding
in aquaculture. However, previous shrimp larvae counting models failed to accurately …

Machine learning-based understanding of aquatic animal behaviour in high-turbidity waters

I Martinez-Alpiste, JB de Tailly… - Expert Systems with …, 2024 - Elsevier
Inspired by the ambitions envisioned in the Fourth Industrial Revolution for aquaculture, also
known as Aquaculture 4.0, the aquaculture (marine animal farming) industry is seeking to …

[HTML][HTML] A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture

N Chirdchoo, S Mukviboonchai, W Cheunta - Intelligent Systems with …, 2024 - Elsevier
This paper presents a novel approach to address the essential challenge of accurately
determining the total weight of shrimp within aquaculture ponds. Precise weight estimation is …