The insect image dataset was extracted using an iterative approach: First, a preliminary detection model identified candidate insects. The primary dataset consists of 29,960 annotated insects representing nine taxa including bees, hoverflies, butterflies and beetles across more than two million images recorded with ten time-lapse cameras mounted over flowers during the summer of 2019. We present a large annotated image dataset of functionally important insect taxa. Deep learning facilitates fast and accurate insect detection and identification, but the lack of training data for coveted deep learning models is a major obstacle for their application. However, extracting ecological data from images is more challenging for insects than for vertebrates because of their small size and great diversity. Image-based monitoring can generate such data cost-efficiently and non-invasively. Reported insect declines have dramatically increased the global demand for standardized insect monitoring data.
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