Thirty years of geometric morphometrics: Achievements, challenges, and the ongoing quest for biological meaningfulness
The foundations of geometric morphometrics were worked out about 30 years ago and have
continually been refined and extended. What has remained as a central thrust and source of …
continually been refined and extended. What has remained as a central thrust and source of …
Computer vision, machine learning, and the promise of phenomics in ecology and evolutionary biology
For centuries, ecologists and evolutionary biologists have used images such as drawings,
paintings and photographs to record and quantify the shapes and patterns of life. With the …
paintings and photographs to record and quantify the shapes and patterns of life. With the …
ALPACA: A fast and accurate computer vision approach for automated landmarking of three‐dimensional biological structures
Landmark‐based geometric morphometrics has emerged as an essential discipline for the
quantitative analysis of size and shape in ecology and evolution. With the ever‐increasing …
quantitative analysis of size and shape in ecology and evolution. With the ever‐increasing …
Measurement of fish morphological features through image processing and deep learning techniques
N Petrellis - Applied Sciences, 2021 - mdpi.com
Featured Application The work described in this paper will support applications that can be
employed in fish culture or in the wild. These applications can be used to monitor fish growth …
employed in fish culture or in the wild. These applications can be used to monitor fish growth …
[HTML][HTML] Artificial intelligence in paleontology
The accumulation of large datasets and increasing data availability have led to the
emergence of data-driven paleontological studies, which reveal an unprecedented picture of …
emergence of data-driven paleontological studies, which reveal an unprecedented picture of …
Deep learning approaches to landmark detection in tsetse wing images
Morphometric analysis of wings has been suggested for identifying and controlling isolated
populations of tsetse (Glossina spp), vectors of human and animal trypanosomiasis in Africa …
populations of tsetse (Glossina spp), vectors of human and animal trypanosomiasis in Africa …
Deep learning to capture leaf shape in plant images: Validation by geometric morphometrics
Plant leaves play a pivotal role in automated species identification using deep learning (DL).
However, achieving reproducible capture of leaf variation remains challenging due to the …
However, achieving reproducible capture of leaf variation remains challenging due to the …
Image based species identification of Globodera quarantine nematodes using computer vision and deep learning
R Thevenoux, LE Van Linh, H Villessèche… - … and Electronics in …, 2021 - Elsevier
Identification of plant parasitic nematode species is usually achieved following
morphobiometric analysis, which requires a certain level of expertise and remains time …
morphobiometric analysis, which requires a certain level of expertise and remains time …
Sashimi: A toolkit for facilitating high‐throughput organismal image segmentation using deep learning
Digitized specimens are an indispensable resource for rapidly acquiring big datasets and
typically must be pre‐processed prior to conducting analyses. One crucial image pre …
typically must be pre‐processed prior to conducting analyses. One crucial image pre …
phenopype: A phenoty** pipeline for Python
MD Lürig - Methods in Ecology and Evolution, 2022 - Wiley Online Library
Digital images are an intuitive way to capture, store and analyse organismal phenotypes.
Many biologists are taking images to collect high‐dimensional phenotypic information from …
Many biologists are taking images to collect high‐dimensional phenotypic information from …