Abstract
In the current study, a region-based approach for object detection is presented that is suitable for handling very small objects and objects in low-resolution images. To address this challenge, an anchoring mechanism for the region proposal stage of the object detection algorithm is proposed, which boosts the performance in the detection of small objects with an insignificant computational overhead. Our method is applicable to the task of robot-assisted disassembly of Waste Electrical and Electronic devices (WEEE) in an industrial environment. Extensive experiments have been conducted in a newly formed device disassembly segmentation dataset with promising results.
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This work was supported by the European Commission under contract H2020-820742 HR-Recycler.
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Athanasiadis, I., Psaltis, A., Axenopoulos, A., Daras, P. (2020). Efficient Fine-Grained Object Detection for Robot-Assisted WEEE Disassembly. In: Vouloutsi, V., Mura, A., Tauber, F., Speck, T., Prescott, T.J., Verschure, P.F.M.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2020. Lecture Notes in Computer Science(), vol 12413. Springer, Cham. https://doi.org/10.1007/978-3-030-64313-3_3
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