Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is har...
详细信息
Colletotrichum kahawae(Coffee Berry Disease)spreads through spores that can be carried by wind,rain,and insects affecting coffee plantations,and causes 80%yield losses and poor-quality coffee *** deadly disease is hard to control because wind,rain,and insects carry *** researchers utilized a deep learning system to identify CBD in coffee cherries at three growth stages and classify photographs of infected and uninfected cherries with 93%accuracy using a random forest *** the dataset is too small and noisy,the algorithm may not learn data patterns and generate accurate *** overcome the existing challenge,early detection of Colletotrichum Kahawae disease in coffee cherries requires automated processes,prompt recognition,and accurate *** proposed methodology selects CBD image datasets through four different stages for training and *** to train a model on datasets of coffee berries,with each image labeled as healthy or *** themodel is trained,SHAP algorithmto figure out which features were essential formaking predictions with the proposed *** of these characteristics were the cherry’s colour,whether it had spots or other damage,and how big the Lesions *** inception is important for classification to virtualize the relationship between the colour of the berry is correlated with the presence of *** evaluate themodel’s performance andmitigate excess fitting,a 10-fold cross-validation approach is *** involves partitioning the dataset into ten subsets,training the model on each subset,and evaluating its *** comparison to other contemporary methodologies,the model put forth achieved an accuracy of 98.56%.
Stroke is a leading cause of global population mortality and disability, imposing burdens on patients and caregivers, and significantly affecting the quality of life of patients. Therefore, in this study, we aimed to ...
详细信息
For a company, it is important to know which products to launch to the market that may get the maximal profit. To achieve this goal, companies not only need to consider these products' features, but also need to a...
详细信息
Recently, deep learning neural networks have been widely used in object classification. The process of object classification typically involves extracting features from the point cloud using neural networks and integr...
详细信息
Crude oil prices (COP) profoundly influence global economic stability, with fluctuations reverberating across various sectors. Accurate forecasting of COP is indispensable for governments, policymakers, and stakeholde...
详细信息
A novel cluster-based traffic offloading and user association (UA) algorithm alongside a multi-agent deep reinforcement learning (DRL) based base station (BS) activation mechanism is proposed in this paper. Our design...
详细信息
For point cloud registration, the purpose of this article is to propose a novel centralized random sample consensus (RANSAC) (C-RANSAC) registration with fast convergence and high accuracy. In our algorithm, the novel...
详细信息
The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of informat...
详细信息
The Nong Han Chaloem Phrakiat Lotus Park is a tourist attraction and a source of learning regarding lotus ***,as a training area,it lacks appeal and learning motivation due to its conventional presentation of information regarding lotus *** current study introduced the concept of smart learning in this setting to increase interest and motivation for *** neural networks(CNNs)were used for the classification of lotus plant species,for use in the development of a mobile application to display details about each *** scope of the study was to classify 11 species of lotus plants using the proposed CNN model based on different techniques(augmentation,dropout,and L2)and hyper parameters(dropout and epoch number).The expected outcome was to obtain a high-performance CNN model with reduced total parameters compared to using three different pre-trained CNN models(Inception V3,VGG16,and VGG19)as *** performance of the model was presented in terms of accuracy,F1-score,precision,and recall *** results showed that the CNN model with the augmentation,dropout,and L2 techniques at a dropout value of 0.4 and an epoch number of 30 provided the highest testing accuracy of *** best proposed model was more accurate than the pre-trained CNN models,especially compared to Inception *** addition,the number of total parameters was reduced by approximately 1.80–2.19 *** findings demonstrated that the proposed model with a small number of total parameters had a satisfactory degree of classification accuracy.
Network attacks, such as botnets stealing sensitive data, constitute a critical concern for administrators in the Internet area. Such attacks can be prevented using a network access control (NAC) scheme. However, exis...
详细信息
暂无评论