ECOLOGICAL ADAPTATION AND SPECIES RECOGNITION DRIVES VOCAL EVOLUTION IN NEOTROPICAL SUBOSCINE BIRDS

Plant species recognition from visual data has always been a challenging task for Artificial Intelligence (AI) researchers, due to a number of complications in the task, such as the enormous data to be processed due to vast number of floral species. There are many sources from a plant that can be used as feature aspects for an AI-based model, but features related to parts like leaves are considered as more significant for the task, primarily due to easy accessibility, than other parts like flowers, stems, etc. With this notion, we propose a plant species recognition model based on morphological features extracted from corresponding leaves’ images using the support vector machine (SVM) with adaptive boosting technique. This proposed framework includes the pre-processing, extraction of features and classification into one of the species. Various morphological features like centroid, major axis length, minor axis length, solidity, perimeter, and orientation are extracted from the digital images of various categories of leaves. In addition to this, transfer learning, as suggested by some previous studies, has also been used in the feature extraction process. Various classifiers like the kNN, decision trees, and multilayer perceptron (with and without AdaBoost) are employed on the opensource dataset, FLAVIA, to certify our study in its robustness, in contrast to other classifier frameworks. With this, our study also signifies the additional advantage of 10-fold cross validation over other dataset partitioning strategies, thereby achieving a precision rate of 95.85%.

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Integumentary Colour Allocation in the Stork Family (Ciconiidae) Reveals Short-Range Visual Cues for Species Recognition

Birds ◽

10.3390/birds2010010 ◽

2021 ◽

Vol 2 (1) ◽

pp. 138-146

Author(s):

Eduardo J. Rodríguez-Rodríguez ◽

Juan J. Negro

Keyword(s):

Short Range ◽

Visual Cues ◽

Species Recognition ◽

The Body ◽

Whole Body ◽

Divergent Evolution ◽

Black And White ◽

Extant Species ◽

Chromatic Spectrum ◽

Mixed Species Flocks

The family Ciconiidae comprises 19 extant species which are highly social when nesting and foraging. All species share similar morphotypes, with long necks, a bill, and legs, and are mostly coloured in the achromatic spectrum (white, black, black, and white, or shades of grey). Storks may have, however, brightly coloured integumentary areas in, for instance, the bill, legs, or the eyes. These chromatic patches are small in surface compared with the whole body. We have analyzed the conservatism degree of colouration in 10 body areas along an all-species stork phylogeny derived from BirdTRee using Geiger models. We obtained low conservatism in frontal areas (head and neck), contrasting with a high conservatism in the rest of the body. The frontal areas tend to concentrate the chromatic spectrum whereas the rear areas, much larger in surface, are basically achromatic. These results lead us to suggest that the divergent evolution of the colouration of frontal areas is related to species recognition through visual cue assessment in the short-range, when storks form mixed-species flocks in foraging or resting areas.

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Species Recognition During Substrate-Borne Communication in Nezara viridula (L.) (Pentatomidae: Heteroptera)

Journal of Insect Behavior ◽

10.1007/s10905-011-9272-x ◽

2011 ◽

Vol 24 (6) ◽

pp. 468-487 ◽

Cited By ~ 21

Author(s):

Alenka Žunič ◽

Meta Virant-Doberlet ◽

Andrej Čokl

Keyword(s):

Species Recognition ◽

Nezara Viridula

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