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An accurate and reliable image based fruit detection system is critical for supporting higher level agriculture tasks such as yield mapping and robotic harvesting. This paper presents the use of a state-of-the-art object detection framework, Faster R-CNN, in the context of fruit detection in orchards, including mangoes, almonds and apples. Ablation studies are presented to better understand the practical...
Low cost and easy to use monocular vision systems are able to capture large scale, dense data in orchards, to facilitate precision agriculture applications. Accurate image parsing is required for this purpose, however, operating in natural outdoor conditions makes this a complex task due to the undesirable intra-class variations caused by changes in illumination, pose and tree types, etc. Typically...
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