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arxiv 2202.11372 v1 pith:UTRBE75W submitted 2022-02-23 cs.CV

Localizing Small Apples in Complex Apple Orchard Environments

classification cs.CV
keywords appleapplessmallapproachesattentionmaskcomplexenvironmentsgeneration
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The localization of fruits is an essential first step in automated agricultural pipelines for yield estimation or fruit picking. One example of this is the localization of apples in images of entire apple trees. Since the apples are very small objects in such scenarios, we tackle this problem by adapting the object proposal generation system AttentionMask that focuses on small objects. We adapt AttentionMask by either adding a new module for very small apples or integrating it into a tiling framework. Both approaches clearly outperform standard object proposal generation systems on the MinneApple dataset covering complex apple orchard environments. Our evaluation further analyses the improvement w.r.t. the apple sizes and shows the different characteristics of our two approaches.

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