해충 카운팅의 정확성 향상을 위한 Dual Block 기반의새로운 Mada-CenterNet
A new Mada-CenterNet based on Dual Block to improve accuracy of pest counting
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초록
농업 분야에서 해충에 대한 효과적인 방제는 작물 생산성 향상에 필수적인 요소이다. 해충의 방제를 위해서는 해충의 종류, 발생시기는 물론이며, 해충의 발생량에 대한 정보가 필요하다. 해충의 발생량을 파악하는 방법인 해충 카운팅 관련 선행 연구인,Mada-CenterNet은 변형 가능한 컨볼루션과 멀티스케일 어텐션 퓨전을 활용하여 해충 카운팅의 정확도를 향상시켰으며 해당 분야에서 가장 우수하다고 보고되고 있다. 본 연구에서는 Mada-CenterNet의 트랜스포머 구조인 멀티스케일 어텐션 대체하는 새로운트랜스포머 구조인 듀얼 블록을 적용하였으며, 픽셀 경로와 시맨틱 경로의 교차 어텐션을 통해 더욱 정교한 특징 맵을 추출하였다. 실험 결과, 제안된 모델은 기존 Mada-CenterNet보다 해충 카운팅 정확도가 우수함과 동시에 폐색 문제와 해충의 몸체 손상, 다양한 모습으로 인한 탐지의 어려움을 효과적으로 완화하였다. 기존 해충 카운팅의 방법과 달리, 인력 및 시간 비용을 절감할 수 있다는 장점을 확보할 수 있으며 물체의 계수가 필요한 다른 농업 분야에도 활용이 가능할 것으로 기대된다.
Abstract
Effective pest control in the agricultural field is essential for improving crop productivity. To do so, information onthe type and timing of pests, as well as the amount of pests generated, is required. Mada-CenterNet, a prior studyon pest counting, which is a method of identifying the amount of pest occurrence, has improved the accuracy ofpest counting by utilizing transformable convolution and multiscale attention fusion and is reported to be the best inthe field. In this study, a new transformer structure with a dual block was applied instead of multiscale attention,which is the transformer structure of Mada-CenterNet. More sophisticated feature maps were extracted throughcross-attention of pixel path and semantic path. As a result of the experiment, the proposed model has improved theaccuracy of pest counting. It is better than the existing Mada-CenterNet and effectively alleviates obstructionproblems, damage to pests' bodies, and detection difficulties caused by various appearances. Unlike conventionalpest counting methods, it can secure the advantage of reducing manpower and time costs, and it is expected that itcan be used in other agricultural fields that require counting of objects.
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