Automatic Plant Organ Detection from Images using Convolutional Neural Networks

Nguyễn Thị Thanh Nhàn, Lê Thị Lan, Vũ Hải, Hoàng Văn Sâm


Detecting plant organs from multiple organ images is the first step in a plant identification system. The current researches mainly rely on the assumption that the type of an organ is manually predetermined. Few works have been done on automatic plant organ detection but they are mainly based on hand-designed features. In this paper, we propose a method for automatic plant organ detection using the convolutional neural network. Different experiments on a subset of the PlantClef 2015 have been conducted to evaluate the robustness of the proposed method. The proposed method obtains 27:44% (for seven-organ cases) and 27:69% (for five-organ cases) of improvement in rank-1 over the state-of-the-art work.

DOI: 10.32913/rd-ict.vol1.no39.634


Phát hiện bộ phận cây, nhận dạng cây, học sâu, mạng nơ-ron tích chập.


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