… sugarcane plant is of no use, so it needs to be detected as soon as possible. A novel deep
learning framework approach is proposed in this paper to detect whether a sugarcane plant is …

… Sugarcane disease recognition using deep learning. In 2019 IEEE Eurasia conference on
… A novel deep learning framework approach for sugarcane disease detection. SN Computer …

… gaps in sugarcane disease detection, recognizing the … approaches, such as advanced
image processing techniques, template matching, support vector machines, and deep learning …

… existing gaps in sugarcane disease detection, recog… approaches, such as advanced
image processing techniques, template matching, support vector machines, and deep learning …

… in the early and precise diagnosis of disease. In this study, different methods used for
machine learning (ML) and deep learning (DL) for plant disease diagnosis were reviewed and it …

… for early disease detection to protect crops in time, as cited in the [9]. In this paper, we
propose a novel Efficient deep learning model for enhanced sugarcane disease detection. Our …

… Sugarcane disease identification is conventionally accomplished through manual inspection
of conspicuous symptoms with the naked eye. This process is laborious, necessitates the …

… sugarcane diseases. This study compared the effectiveness … in disease detection, such as
traditional machine learning … of machine learning in agriculture beyond sugarcane disease …

… a deep learning approach and its utilization to identify weeds in sugarcane fields. The work
… of developing an intelligent identification system for weeds and sugarcane using images …

… diseases of sugarcane leaves, this research suggests an attention-based multilevel deep
learning … Plant disease diagnosis systems have been in discussion for a long and are …