Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 4 of 4
Full-Text Articles in Life Sciences
Characterization Of Tea (Camellia Sinensis) Granules For Quality Grading Using Computer Vision System, Md Towfiqur Rahman, Sabiha Ferdous, Mariya Sultana Jenin, Tanjina Rahman Mim, Masud Alam, Muhammad Rashed Al Mamun
Characterization Of Tea (Camellia Sinensis) Granules For Quality Grading Using Computer Vision System, Md Towfiqur Rahman, Sabiha Ferdous, Mariya Sultana Jenin, Tanjina Rahman Mim, Masud Alam, Muhammad Rashed Al Mamun
Department of Biological Systems Engineering: Papers and Publications
Tea (Camellia sinensis) has been found as an important medicinal beverage for human which is consumed all over the world. Primarily, the majority of tea is being cultivated in Asia and Africa, however it is commercially produced by more than 60 countries. Though substantial amount is produced, its processing system is still underdeveloped which leads to decrease in export opportunity as well as low monetary value. Moreover, the traditional method of tea grading and sorting is laborious, inefficient, and costly which ultimately produces the low-quality heterogeneous products. Processing and grading of tea granules after drying is very important …
Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu
Development Of Deep Learning Neural Network For Ecological And Medical Images, Shaobo Liu
Dissertations
Deep learning in computer vision and image processing has attracted attentions from various fields including ecology and medical image. Ecologists are interested in finding an effective model structure to classify different species. Tradition deep learning model use a convolutional neural network, such as LeNet, AlexNet, VGG models, residual neural network, and inception models, are first used on classifying bee wing and butterfly datasets. However, insufficient data sample and unbalanced samples in each class have caused a poor accuracy. To make improvement the test accuracy, data augmentation and transfer learning are applied. Recently developed deep learning framework based on mathematical morphology …
A Bibliometric Analysis Of Plant Disease Classification With Artificial Intelligence Based On Scopus And Wos, Shivali Amit Wagle, Harikrishnan R
A Bibliometric Analysis Of Plant Disease Classification With Artificial Intelligence Based On Scopus And Wos, Shivali Amit Wagle, Harikrishnan R
Library Philosophy and Practice (e-journal)
The maneuver of Artificial Intelligence (AI) techniques in the field of agriculture help in the classification of diseases. Early prediction of the disease benefits in taking relevant management steps. This is an important step towards controlling the disease growth that will yield good quality products to fulfill the global food demand. The main objective of this paper is to study the extent of research work done in this area of plant disease classification. The paper discusses the bibliometric analysis of plant disease classification with AI in Scopus and Web of Science core collection (WOS) database in analyzing the research by …
Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii
Neural Network Supervised And Reinforcement Learning For Neurological, Diagnostic, And Modeling Problems, Donald Wunsch Iii
Masters Theses
“As the medical world becomes increasingly intertwined with the tech sphere, machine learning on medical datasets and mathematical models becomes an attractive application. This research looks at the predictive capabilities of neural networks and other machine learning algorithms, and assesses the validity of several feature selection strategies to reduce the negative effects of high dataset dimensionality. Our results indicate that several feature selection methods can maintain high validation and test accuracy on classification tasks, with neural networks performing best, for both single class and multi-class classification applications. This research also evaluates a proof-of-concept application of a deep-Q-learning network (DQN) to …