A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)

Borlinghaus, Parzival; Tausch, Frederic; Rettenberger, Luca

doi:10.1016/j.atech.2022.100135

Cited by 4 publications

(1 citation statement)

References 9 publications

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“…Observation, please see video footage in our data). As mentioned earlier, these counters allow detection of other bee species such as non‐ Apis bees with a simple adaptation of the algorithm (Borlinghaus et al., 2023; Knauer et al., 2022), and of course tracking of individual honey bees to follow their entire lifespan (Chen et al., 2012). Similar if not superior to what is currently described in OECD GD No.…”

Section: Most Recent Advancesmentioning

confidence: 99%

Making way for the implementation of automated bee counters in regulatory risk assessment

Odemer,

Jakoby,

Barth

et al. 2024

J Applied Entomology

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Measuring adverse effects on honey bees and their colonies requires a suitable methodology. For example, due to the large number of bees in a hive and the foraging activity, measuring the mortality of individuals is a difficult task that has not yet been adequately addressed. Knowing the natural daily mortality rate of a bee colony would be of great benefit in assessing whether and to what extent external influences and stress factors affect mortality. More precise mortality data could in turn help refining specific protection goals for regulatory purpose. The European Food Safety Authority recently published a document that estimated such mortality rates based on a systematic literature review, but none of these rates were assessed from continuous monitoring of colonies. Currently, bee mortality is routinely evaluated with various types of dead bee traps that prevent deceased bees from being removed from the colony. Both the literature review and the dead bee traps are relevant to regulatory risk assessment, but in our opinion are not describing the total mortality. Bee counters capable of precisely determining daily loss rates meet the above points and combine them with generating automated and continuous monitoring data. Lately, the field has gained a lot of importance in research and technological advances offer new possibilities in regulatory risk assessment. We will highlight these possibilities and discuss their future application in practice.

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Section: Most Recent Advancesmentioning

confidence: 99%

Making way for the implementation of automated bee counters in regulatory risk assessment

Odemer,

Jakoby,

Barth

et al. 2024

J Applied Entomology

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Species-Agnostic Patterned Animal Re-identification by Aggregating Deep Local Features

Nepovinnykh,

Chelak,

Eerola

et al. 2024

Int J Comput Vis

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Access to large image volumes through camera traps and crowdsourcing provides novel possibilities for animal monitoring and conservation. It calls for automatic methods for analysis, in particular, when re-identifying individual animals from the images. Most existing re-identification methods rely on either hand-crafted local features or end-to-end learning of fur pattern similarity. The former does not need labeled training data, while the latter, although very data-hungry typically outperforms the former when enough training data is available. We propose a novel re-identification pipeline that combines the strengths of both approaches by utilizing modern learnable local features and feature aggregation. This creates representative pattern feature embeddings that provide high re-identification accuracy while allowing us to apply the method to small datasets by using pre-trained feature descriptors. We report a comprehensive comparison of different modern local features and demonstrate the advantages of the proposed pipeline on two very different species.

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Introducing Pollenyzer: An app for automatic determination of colour diversity for corbicular pollen loads

Borlinghaus

Jung

Odemer

2023

Smart Agricultural Technology

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A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)

Cited by 4 publications

References 9 publications

Making way for the implementation of automated bee counters in regulatory risk assessment

Making way for the implementation of automated bee counters in regulatory risk assessment

Species-Agnostic Patterned Animal Re-identification by Aggregating Deep Local Features

Introducing Pollenyzer: An app for automatic determination of colour diversity for corbicular pollen loads

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