Search Results - (( java implementation tree algorithm ) OR ( knowledge 3d visualization algorithm ))

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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The development of level of detail (LOD) technique in 3D computer graphics application by Ismail, Nor Anita Fairos, Daman, Daut, Mohd. Rahim, Mohd. Shafry

“…Drastic growth in computer simulation complexity and 3D scanning technology has boosted the size of geometry data sets used in visualization. …”
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows by Zhang, Shasha, Dong, Qiming, Yasin, Megat Al Imran, Fang, Ng Chwee

“…During the feature extraction part, different machine-learning models are applied: Bidirectional Encoder Representations from Transformers (BERT) or Enhanced Representation through Knowledge Integration (ERNIE) for text; Convolutional Recurrent Neural Network (CRNN), and Bidirectional Long Short-Term Memory (Bi-LSTM) for audio; and Residual Neural Network (ResNet50) and Inflated 3D Convolutional Network (I3D) for video. …”
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Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using Dempster–Shafer theory by Saeidi, Vahideh, Pradhan, Biswajeet, Idrees, Mohammed Oludare, Abd Latif, Zulkiflee

“…This study proves that DST is a time- and cost-effective method for accurate land-cover feature identification and extraction without the need for a prior knowledge of the scene. Furthermore, the ability to generate ot- er products like certainty, conflict, and maximum probability maps for better visual understanding of the decision process makes it more reliable for applications such as urban planning, forest management, 3-D feature extraction, and map updating.…”
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