Out[3]= Gather the elements by their class number: In[4]:= Out[4]= Train the ClassifierFunction on some strings: In[1]:= In[2]:= Out[2]= In[3]:= Out[3]= Gather the elements by their class number: In[4]:= Out[4]= Scope(11) Options(10) Applications(3) See...
Application of fuzzy c-means clustering method to classify wheat leaf images based on the presence of rust disease. In Proceedings of the 3rd International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2014, pages 277-284. Springer, 2015....
Semantic Supervised Clustering Approach to Classify Land Cover in Remotely Sensed ImagesGIS applications involve applying classification algorithms to remotely sensed images to determine information about a specific region on the Earth's surface. These images are very useful sources of geographical data ...
When merging clusters, it was found that the proposed method could lead to more than 12% improvement in classifier accuracy while retaining resolution of 4 tasks. Conclusion Hierarchical clustering methods are relevant to developing classifiers of motor activities from data recorded using wearable ...
We used the silhouette coefficient36 to evaluate the clustering accuracy for both our method and expression-based integration. We only considered cell types that can be mapped to the Cell Ontology term in the classification evaluation (Fig. 4e). We considered all cell types in the unsupervised ...
An innovative approach to classify and retrieve text documents using feature extraction and Hierarchical clustering based on ontology Data retrieval is a key process of acquiring information as per requirement. The necessity of proper information has increased. The most basic tools which ... AR Patil...
Weather classification from single images plays an important role in many outdoor computer vision applications, while it has not been thoroughly studied. Despite existing methods have achieved great success under the supervision of we...
CNN-BiLSTM together with the binary version of MRFO is implemented to determine an optimal combination of the most significant neurophysiological inputs that account for CWL classification. Furthermore, a version of Fuzzy C-Means (FCM) entitled optimal clustering strategy (OCS) is also implemented ...
(S2FCM) clustering method to reduce feature dimension.This method guides with the most subjection.On one hand it keeps fuzzy clustering effect,and on the other hand it can enhance the constringency pace and improve the correctness of feature selection.Here we also apply the ameliorated subjection...
2D precise the origin of this clustering, revealing that the LWB section and the healthy reference are characterized by the presence of signals from the non-mineralized collagen fibres (yellow star), while the MWB section of biopsy#2 presents peaks coming from both the cellular soft phase and ...