Deep learning as a tool for ecology and evolution

ML Borowiec, RB Dikow, PB Frandsen… - Methods in Ecology …, 2022 - Wiley Online Library
Deep learning is driving recent advances behind many everyday technologies, including
speech and image recognition, natural language processing and autonomous driving. It is …

Identification of fish species and targeted genetic modifications based on DNA analysis: State of the art

E Cermakova, S Lencova, S Mukherjee, P Horka… - Foods, 2023 - mdpi.com
Food adulteration is one of the most serious problems regarding food safety and quality
worldwide. Besides misleading consumers, it poses a considerable health risk associated …

Revisiting molecular techniques for the authentication of mackerels in commercial products. Approaches to prevent seafood fraud

L Lorusso, A Mottola, R Piredda, A Di Pinto… - Trends in Food Science …, 2024 - Elsevier
Background Seafood fraud involves mislabeling and false claims. To avoid this deceptive
practice, authentication techniques, including DNA-based methods, have been developed …

[HTML][HTML] An advanced Bangladeshi local fish classification system based on the combination of deep learning and the internet of things (IoT)

MA Ahmed, MS Hossain, W Rahman, AH Uddin… - Journal of Agriculture …, 2023 - Elsevier
Fish classification leads to the automated machine-based fish separation system. In terms of
classification and real-time data monitoring, deep learning and the Internet of Things (IoT) …

Novel modified convolutional neural network and FFA algorithm for fish species classification

P Prasenan, CD Suriyakala - Journal of Combinatorial Optimization, 2023 - Springer
Biologists and marine ecologists' vital task is to classify fish species regularly to assess the
relative profusion of fish species in their native environments and track population …

Evaluating the method reproducibility of deep learning models in the biodiversity domain

W Ahmed, VK Kommineni, B König-Ries… - arXiv preprint arXiv …, 2024 - arxiv.org
Artificial Intelligence (AI) is revolutionizing biodiversity research by enabling advanced data
analysis, species identification, and habitats monitoring, thereby enhancing conservation …

Atrous Pyramid GAN Segmentation Network for Fish Images with High Performance

X Zhou, S Chen, Y Ren, Y Zhang, J Fu, D Fan, J Lin… - Electronics, 2022 - mdpi.com
With the development of computer science technology, theory and method of image
segmentation are widely used in fish discrimination, which plays an important role in …

[PDF][PDF] Comparison of Machine Learning Algorithms for Species Family Classification using DNA Barcode.

LS Riza, MAF Rahman, Y Prasetyo, MI Zain… - Knowl. Eng. Data …, 2023 - researchgate.net
The development of living specimen processing technology [1] in recent decades has
created many biological data, including Deoxyribonucleic Acid (DNA) sequence data. The …

AI-Powered Biodiversity Assessment: Species Classification via DNA Barcoding and Deep Learning

L Nanni, D Cuza, S Brahnam - Technologies, 2024 - researchportal.hw.ac.uk
Only 1.2 million out of an estimated 8.7 million species on Earth have been fully classified
through taxonomy. As biodiversity loss accelerates, ecologists are urgently revising …

Automated DNA Barcoding: A Computational Approach to Fish Species Identification

FQ López - FishTaxa-Journal of Fish Taxonomy, 2024 - fishtaxa.com
Molecular technologies like DNA metabarcoding, which offer a useful identifying tool for
biomonitoring and conservation initiatives, are advantageous to biodiversity research …