Search Results - (( knowledge 3d visualization algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Parallel visualization approach of a 3D heart model by Malekpour, A., Ling, T.C., Lim, W.C.

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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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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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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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