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A Clustering-Driven Approach to Predict the Traffic Load of Mobile Networks for the Analysis of Base Stations Deployment.

, , , , and . J. Sens. Actuator Networks, 9 (4): 53 (2020)

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Analog layout constraints resolution and shape function generation using Satisfiability Modulo Theories., , , , and . DTIS, page 1-6. IEEE, (2015)LiteSeg: A Novel Lightweight ConvNet for Semantic Segmentation., , and . DICTA, page 1-7. IEEE, (2019)A Platform for Placement of Analog Integrated Circuits Using Satisfiability Modulo Theories., , , , and . Journal of Circuits, Systems, and Computers, 25 (5): 1650047:1-1650047:31 (2016)Comparative Study on Deep Convolution Neural Networks DCNN-Based Offline Arabic Handwriting Recognition., , and . IEEE Access, (2020)Improved features and dynamic stream weight adaption for robust Audio-Visual Speech Recognition framework., , and . Digit. Signal Process., (2019)Neural networks for maximum likelihood clustering., and . Signal Process., 36 (1): 111-126 (1994)Classified vector quantization using variance classifier and maximum likelihood clustering., and . Pattern Recognit. Lett., 15 (1): 49-55 (1994)Novel low-band phase representation for low bit-rate speech coding., , and . INTERSPEECH, page 1669-1672. ISCA, (2007)Improved security of neural cryptography using don't-trust-my-partner and error prediction., and . IJCNN, page 121-127. IEEE Computer Society, (2009)Pareto front analog layout placement using Satisfiability Modulo Theories., , , , and . DATE, page 1411-1416. IEEE, (2016)