Semantic versus instance segmentation in microscopic algae detection
Microscopic algae segmentation, specifically of diatoms, is an essential procedure for water
quality assessment. The segmentation of these microalgae is still a challenge for computer …
quality assessment. The segmentation of these microalgae is still a challenge for computer …
Automated diatom classification (Part B): a deep learning approach
Diatoms, a kind of algae microorganisms with several species, are quite useful for water
quality determination, one of the hottest topics in applied biology nowadays. At the same …
quality determination, one of the hottest topics in applied biology nowadays. At the same …
Deep learning-based diatom taxonomy on virtual slides
Deep convolutional neural networks are emerging as the state of the art method for
supervised classification of images also in the context of taxonomic identification. Different …
supervised classification of images also in the context of taxonomic identification. Different …
Automatic taxonomic identification based on the Fossil Image Dataset (> 415,000 images) and deep convolutional neural networks
The rapid and accurate taxonomic identification of fossils is of great significance in
paleontology, biostratigraphy, and other fields. However, taxonomic identification is often …
paleontology, biostratigraphy, and other fields. However, taxonomic identification is often …
Accurate classification of algae using deep convolutional neural network with a small database
The variations in algal diversity and populations are essential for evaluating aquatic system
health. However, manual classification is time-consuming and labor-intensive. As AI has …
health. However, manual classification is time-consuming and labor-intensive. As AI has …
A low-cost automated digital microscopy platform for automatic identification of diatoms
Featured Application Development of a fully operative low-cost automated digital
microscope for the detection of diatoms by applying deep learning. Abstract Currently …
microscope for the detection of diatoms by applying deep learning. Abstract Currently …
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 …
Learning diatoms classification from a dry test slide by holographic microscopy
Diatoms are among the dominant phytoplankters in marine and freshwater habitats, and
important biomarkers of water quality, making their identification and classification one of the …
important biomarkers of water quality, making their identification and classification one of the …
Tackling inter-class similarity and intra-class variance for microscopic image-based classification
Automatic classification of aquatic microorganisms is based on the morphological features
extracted from individual images. The current works on their classification do not consider …
extracted from individual images. The current works on their classification do not consider …
General image fiber tool: A concept for automated evaluation of fiber diameters in SEM images
A Götz, V Senz, W Schmidt, J Huling, N Grabow… - Measurement, 2021 - Elsevier
Fiber imaging is becoming increasingly important in various fields. The current standard
method of quality assurance is the manual quantification of fiber diameters in Scanning …
method of quality assurance is the manual quantification of fiber diameters in Scanning …