|
|
|
|
|
Abdul Rahaman Wahab Sait and Ali Mohammad Alorsan Bani Awad
Coronary artery disease (CAD) is the most prevalent form of cardiovascular disease that may result in myocardial infarction. Annually, it leads to millions of fatalities and causes billions of dollars in global economic losses. Limited resources and comp...
ver más
|
|
|
|
|
|
|
|
|
|
|
Huizhong Xiong, Xiaotong Gao, Ningyi Zhang, Haoxiong He, Weidong Tang, Yingqiu Yang, Yuqian Chen, Yang Jiao, Yihong Song and Shuo Yan
A novel deep learning model, DiffuCNN, is introduced in this paper, specifically designed for counting tobacco lesions in complex agricultural settings. By integrating advanced image processing techniques with deep learning methodologies, the model signi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Huiru Zhou, Qiang Lai, Qiong Huang, Dingzhou Cai, Dong Huang and Boming Wu
The severity of rice blast and its impacts on rice yield are closely related to the inoculum quantity of Magnaporthe oryzae, and automatic detection of the pathogen spores in microscopic images can provide a rapid and effective way to quantify pathogen i...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ruicheng Gao, Zhancai Dong, Yuqi Wang, Zhuowen Cui, Muyang Ye, Bowen Dong, Yuchun Lu, Xuaner Wang, Yihong Song and Shuo Yan
In this study, a deep-learning-based intelligent detection model was designed and implemented to rapidly detect cotton pests and diseases. The model integrates cutting-edge Transformer technology and knowledge graphs, effectively enhancing pest and disea...
ver más
|
|
|
|
|
|
|
|
|
|
|
Ping Dong, Kuo Li, Ming Wang, Feitao Li, Wei Guo and Haiping Si
In addition to the conventional situation of detecting a single disease on a single leaf in corn leaves, there is a complex phenomenon of multiple diseases overlapping on a single leaf (compound diseases). Current research on corn leaf disease detection ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhichao Chen, Hongping Zhou, Haifeng Lin and Di Bai
The tea industry, as one of the most globally important agricultural products, is characterized by pests and diseases that pose a serious threat to yield and quality. These diseases and pests often present different scales and morphologies, and some pest...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xuejun Yue, Haifeng Li, Qingkui Song, Fanguo Zeng, Jianyu Zheng, Ziyu Ding, Gaobi Kang, Yulin Cai, Yongda Lin, Xiaowan Xu and Chaoran Yu
Existing disease detection models for deep learning-based monitoring and prevention of pepper diseases face challenges in accurately identifying and preventing diseases due to inter-crop occlusion and various complex backgrounds. To address this issue, w...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergenc...
ver más
|
|
|
|
|
|
|
|
|
|
|
Utpal Barman, Parismita Sarma, Mirzanur Rahman, Vaskar Deka, Swati Lahkar, Vaishali Sharma and Manob Jyoti Saikia
Invading pests and diseases always degrade the quality and quantity of plants. Early and accurate identification of plant diseases is critical for plant health and growth. This work proposes a smartphone-based solution using a Vision Transformer (ViT) mo...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yuanyuan Shao, Shengheng Ji, Guantao Xuan, Yanyun Ren, Wenjie Feng, Huijie Jia, Qiuyun Wang and Shuguo He
The objective is to develop a portable device capable of promptly identifying root rot in the field. This study employs hyperspectral imaging technology to detect root rot by analyzing spectral variations in chili pepper leaves during times of health, in...
ver más
|
|
|
|
|
|