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Full-Text Articles in Computer Sciences
A Deep Fuzzy Classifier Based On Feature Transform And Reconstruction, Rui Yin, Wei Lu, Jianhua Yang
A Deep Fuzzy Classifier Based On Feature Transform And Reconstruction, Rui Yin, Wei Lu, Jianhua Yang
Journal of System Simulation
Abstract: To obtain a classifier with good classification accuracy and interpretability, a deep fuzzy classifier based on feature transform and reconstruction (FR-DFC) is proposed. In FR-DFC, several fuzzy systems (FT_FS) for feature transform and a multi-prototype fuzzy classification system (MPRFD_FS) are stacked together to realize the classification process of the model, based on the hierarchically stacked thought originated from deep learning. Specifically, the stacked FT_FSs explore the hidden features in the data by transferring data from the original data space to the high-level feature space. MPRFD_FS, on the other hand, implements classification based on multiple prototypes that characterize the distribution …
Classification Of Beef And Pork Images Based On Color Features And Pseudo Nearest Neighbor Rule, Ahmad Awaluddin Baiti, Muhammad Fachrie, Saucha Diwandari
Classification Of Beef And Pork Images Based On Color Features And Pseudo Nearest Neighbor Rule, Ahmad Awaluddin Baiti, Muhammad Fachrie, Saucha Diwandari
Elinvo (Electronics, Informatics, and Vocational Education)
This research is motivated by the need for halal foods in Muslim society with the purpose of avoiding non-halal foods, such as pork, that are sold in the market. Although beef and pork basically have different characteristics, not all Muslims know the differences. Moreover, people nowadays sell beef mixed with pork to obtain more profits. Hence, this paper proposed the implementation of the Pseudo-Nearest Neighbor Rule (PNNR) in classifying images of beef and pork slices based on color features. Based on the image dataset that has been collected, the very significant difference that can be identified visually between beef and …
Signature Identification And Verification Systems: A Comparative Study On The Online And Offline Techniques, Nehal Hamdy Al-Banhawy, Heba Mohsen, Neveen I. Ghali Prof.
Signature Identification And Verification Systems: A Comparative Study On The Online And Offline Techniques, Nehal Hamdy Al-Banhawy, Heba Mohsen, Neveen I. Ghali Prof.
Future Computing and Informatics Journal
Handwritten signature identification and verification has become an active area of research in recent years. Handwritten signature identification systems are used for identifying the user among all users enrolled in the system while handwritten signature verification systems are used for authenticating a user by comparing a specific signature with his signature that is stored in the system. This paper presents a review for commonly used methods for preprocessing, feature extraction and classification techniques in signature identification and verification systems, in addition to a comparison between the systems implemented in the literature for identification techniques and verification techniques in online and …
Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi
Machine Learning Pipeline For Exoplanet Classification, George Clayton Sturrock, Brychan Manry, Sohail Rafiqi
SMU Data Science Review
Planet identification has typically been a tasked performed exclusively by teams of astronomers and astrophysicists using methods and tools accessible only to those with years of academic education and training. NASA’s Exoplanet Exploration program has introduced modern satellites capable of capturing a vast array of data regarding celestial objects of interest to assist with researching these objects. The availability of satellite data has opened up the task of planet identification to individuals capable of writing and interpreting machine learning models. In this study, several classification models and datasets are utilized to assign a probability of an observation being an exoplanet. …
Multiple-Attribute Entity Recommendation Based On Classification, Meina Song, Xuejun Zhao, Haihong E
Multiple-Attribute Entity Recommendation Based On Classification, Meina Song, Xuejun Zhao, Haihong E
Journal of System Simulation
Abstract: In the process of exploring entity recommendation, the entity containing diverse attributes has gained more and more attention. Most of the current researchers mainly select one attribute, and embody it in the related algorithms and their extensions even though the entity is combined with multiple attributes in entity recommendation. In this paper, on the basis of the classification method, we delve into physical properties of the recommended entities, divide entity’s attribute information network into multiple sub ones. In sub information network, bounded by the amount of attributes, the single attribute and even multiple attributes can be diverted into diverse …
Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang
Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang
Journal of the Arkansas Academy of Science
The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.
Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr
Process Models Discovery And Traces Classification: A Fuzzy-Bpmn Mining Approach., Kingsley Okoye Dr, Usman Naeem Dr, Syed Islam Dr, Abdel-Rahman H. Tawil Dr, Elyes Lamine Dr
Journal of International Technology and Information Management
The discovery of useful or worthwhile process models must be performed with due regards to the transformation that needs to be achieved. The blend of the data representations (i.e data mining) and process modelling methods, often allied to the field of Process Mining (PM), has proven to be effective in the process analysis of the event logs readily available in many organisations information systems. Moreover, the Process Discovery has been lately seen as the most important and most visible intellectual challenge related to the process mining. The method involves automatic construction of process models from event logs about any domain …