Landmark Detection For Tsetse Fly

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Automated Landmark Detection for 14,354 Tsetse Fly Wings

Accurate Morphometric Data

By [source]

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About this dataset

This dataset contains the coordinates of 11 anatomical landmarks on 14,354 pairs of field-collected tsetse fly wings. Accurately located with automatic deep learning by a two-tier method, this identification process is essential for those conducting morphological or biological research on the species Glossina pallidipes and G. m. morsitans. An accurate capture of these data points is both difficult and time-consuming — making our employee double tier method an invaluable resource for any researchers in need! Columns include morphology data such as wing length measurements, landmark locations, host collections, collection dates/months/years, morphometric data strings and more — allowing you to uncover new insights into these fascinating insects through detailed analysis! Unlock new discoveries within the natural world by exploring this exciting dataset today — from gaining insight into tsetse fly wing characteristics to larger implications regarding biology and evolution— you never know what exciting findings await!

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How to use the dataset

Step 1: Download the data from Kaggle. Unzip it and open it in your favorite spreadsheet software (e.g., Excel or Google Sheets).

Step 2: Become familiar with the two available data fields in ALDTTFW — wing length measurement ‘wlm' and distance between left and right wings ‘dis_l'. These two pieces of information are extremely helpful when analyzing wingpair morphology within a larger sample size as they allow researchers to identify discrepancies between multiple sets of wings in a given group quickly and easily.

**Step 3: ** Take note of each wing's landmark coordinates, which can be found under columns lmkl through lmkr — there are 11 total areas measured per each individual left and right wing (e.g., ‘L x1’: X coordinate of first landmark on the left wing provides anatomical precision)

**Step 4: ** Make sure that both wings have been labeled accurately by checking out their respective quality grades found under columns 'left_good' and 'right_good'. A grade of either 0 or 1 indicates whether background noise is present, which could result in inaccurate set of landmark points later on during analysis; thus grade should always be 1 before continuing with further steps

** Step 5 :** Calculate pertinent averages from given values such as overall wing span measurement or anatomic landmarks distances – these averages shall tell us if there exist particular traits distinguishing among multiple groups gathered together for comparison purposes

Lastly – always double check accuracy! It is advised that you reference previously collected literature regarding locations specific anatomic landmarks prior making any final conclusions from your

Research Ideas

• Comparing the morphology of tsetse fly wings across different host species, locations, and/or collections.
• Creating classification algorithms for morphometric analysis that use deep learning architectures for automatic landmark detection.
• Developing high resolution identifying methods (or markers) to distinguish between tsesse fly species and subspecies based on their wing anatomy landmarks

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: morphometric_data.csv

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .