How does the Internet of Things (IoT) help in microalgae biorefinery?
Microalgae biorefinery is a platform for the conversion of microalgal biomass into a variety of
value-added products, such as biofuels, bio-based chemicals, biomaterials, and bioactive …
value-added products, such as biofuels, bio-based chemicals, biomaterials, and bioactive …
Machine learning and deep learning based computational approaches in automatic microorganisms image recognition: methodologies, challenges, and …
Microorganisms or microbes comprise majority of the diversity on earth and are extremely
important to human life. They are also integral to processes in the ecosystem. The process of …
important to human life. They are also integral to processes in the ecosystem. The process of …
Deep learning for microalgae classification
Microalgae are unicellular organisms that presents limited physical characteristics such as
size, shape or even the present structures. Classifying them manually may require great …
size, shape or even the present structures. Classifying them manually may require great …
Survey of automatic plankton image recognition: challenges, existing solutions and future perspectives
T Eerola, D Batrakhanov, NV Barazandeh… - Artificial Intelligence …, 2024 - Springer
Planktonic organisms including phyto-, zoo-, and mixoplankton are key components of
aquatic ecosystems and respond quickly to changes in the environment, therefore their …
aquatic ecosystems and respond quickly to changes in the environment, therefore their …
Phytoplankton detection and recognition in freshwater digital microscopy images using deep learning object detectors
Water quality can be negatively affected by the presence of some toxic phytoplankton
species, whose toxins are difficult to remove by conventional purification systems. This …
species, whose toxins are difficult to remove by conventional purification systems. This …
The feasibility of automated identification of six algae types using feed-forward neural networks and fluorescence-based spectral-morphological features
Harmful algae blooms are a growing global concern since they negatively affect the quality
of drinking water. The gold-standard process to identify and enumerate algae requires …
of drinking water. The gold-standard process to identify and enumerate algae requires …
Fully automatic detection and classification of phytoplankton specimens in digital microscopy images
D Rivas-Villar, J Rouco, R Carballeira… - Computer Methods and …, 2021 - Elsevier
Background and objective The proliferation of toxin-producing phytoplankton species can
compromise the quality of the water sources. This contamination is difficult to detect, and …
compromise the quality of the water sources. This contamination is difficult to detect, and …
[HTML][HTML] 基于改进YOLO v7 的微藻轻量级检测方法
吴志高， 陈明 - 大连海洋大学学报, 2023 - xuebao.dlou.edu.cn
为了解决传统的微藻检测方法依赖于复杂的设备和大量的人工操作, 不仅耗时长且检测结果易受
检测人员技术经验影响等问题, 结合微藻显微图像特征, 采用K-means++ 算法聚类锚框 …
检测人员技术经验影响等问题, 结合微藻显微图像特征, 采用K-means++ 算法聚类锚框 …
Toward embedded sensing automation and miniaturization for portable smart cost-effective algae monitor
Y Liao, N Yu, D Tian, Y Wang, S Li, Z Li - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
As an important indicator of water pollution, algae are highly sensitive to changes in their
environment and respond to a wide range of pollutants, they provide an early caution signal …
environment and respond to a wide range of pollutants, they provide an early caution signal …
Automatic detection of freshwater phytoplankton specimens in conventional microscopy images
Water safety and quality can be compromised by the proliferation of toxin-producing
phytoplankton species, requiring continuous monitoring of water sources. This analysis …
phytoplankton species, requiring continuous monitoring of water sources. This analysis …