Search Results - (( automatic classification parallel algorithm ) OR ( code classifications clustering algorithm ))

Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

“…This method resulted around 99% of classification rate. To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Classic bag of visual words algorithm is based on k-means clustering and every SIFT features belongs to one cluster and it leads to decreasing classification results. …”
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Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

“…In order to make financial big data generate business value and improve the information application level of financial management, aiming at the high error rate of current financial data classification system, this article adopts the fuzzy clustering algorithm to classify financial data automatically, and adopts the local outlier factor algorithm with neighborhood relation (NLOF) to detect abnormal data. …”
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

“…Beside that, classic bag of visual words algorithm (BoVW) is based on kmeans clustering and every SIFT feature belongs to one cluster and it leads to decreasing classification results. …”
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Classification of metamorphic virus using n-grams signatures by A Hamid, Isredza Rahmi, Md Sani, Nur Sakinah, Abdullah, Zubaile, Mohd Foozy, Cik Feresa, Kipli, Kuryati

“…The first step is the classification model to cluster the metamorphic virus using TF-IDF technique. …”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis by Rochin Demong, Nur Atiqah, Mohamed Razali, Murni Zarina, Kamaruddin, Juliana Noor, Shamsuddin, Sazwan, Awang, Nor Ain, Kamarudin, Norjuliatie, Wan Othman, Noor Faradilla

“…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms by Choong, Chun Sern

“…The ensemble learning technique, changes of activation function in Neural Network as well as the unsupervised learning (k-means clustering algorithm and Friis Transmission Equation) was also applied to classify the multiclass classification in pallet-level. …”
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Projecting named entity tags from a resource rich language to a resource poor language by Zamin, Norshuhani, Oxley, Alan, Abu Bakar, Zainab

“…Named Entities (NE) are the prominent entities appearing in textual documents.Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

“…Named Entities (NE) are the prominent entities appearing in textual documents. Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

“…Named Entities (NE) are the prominent entities appearing in textual documents. Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language by Zamin, N., Oxley, A., Bakar, Z.A.

“…Named Entities (NE) are the prominent entities appearing in textual documents. Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Improving brain tumor segmentation in MRI images through enhanced convolutional neural networks by Ayomide, Kabirat Sulaiman, Mohd Aris, Teh Noranis, Zolkepli, Maslina

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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
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An automated multimodal white matter hyperintensities identification in MRI brain images using image processing / Iza Sazanita Isa by Isa, Iza Sazanita

“…This research proposes a method for automatic detection of WMH in white matter (WM) tissue for MRI images. …”
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Short term load forecasting using a hybrid neural network by Yap K.S., Abidin I.Z., Lim C.P., Shah M.S.

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