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Titlebook: Artificial Intelligence and Evolutionary Computations in Engineering Systems; Computational Algori S. Chandramohan,Bala Venkatesh,C. Sharme

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樓主: 喜悅
31#
發(fā)表于 2025-3-26 22:47:16 | 只看該作者
32#
發(fā)表于 2025-3-27 04:12:57 | 只看該作者
Hardware-Based Document Image Thresholding Techniques Using DSP Builder and Simulink,ng Altera Cyclone? V FPGA kit. Initially, show-through noise from the document images was removed using the thresholding method in the OpenCV environment and compared the results with the FPGA results. Then, we created a library file for Cyclone? V 5CSEMA5F31C6N series, as board block in DSP builder
33#
發(fā)表于 2025-3-27 05:37:22 | 只看該作者
Performance Analysis of MIMO and Massive MIMO with Rayleigh, Rician and Nakagami Channels,ied utilizing Time Division multiplexing. MIMO overcomes bandwidth restrictions with its channel state information and multiple antennas. Massive MIMO uses large-scale antenna systems and are capable of improving the channel capability. Extra antennas improve the throughput and energy efficiency. Th
34#
發(fā)表于 2025-3-27 13:05:02 | 只看該作者
Event Detection and Control of Blood Glucose Levels Using Deep Neural Network,. Diabetes is also leading to many short-term and long-term complications if it is not managed properly. Therefore, monitoring and control of glucose level plays a vital part in diabetic research. This paper deals with the classification of glucose levels of the patients based on their clinical data
35#
發(fā)表于 2025-3-27 17:22:50 | 只看該作者
36#
發(fā)表于 2025-3-27 21:01:04 | 只看該作者
Lucio Davide Spano,Federico Maria Caut of maximum (SoM) methods are implemented in this work for estimation of flux linkage for SRM. The estimated flux linkage profile obtained using different defuzzification methods are evaluated and the results are analyzed. It is observed that the results from the centroid method of defuzzification are in good agreement with the original values.
37#
發(fā)表于 2025-3-27 23:11:34 | 只看該作者
38#
發(fā)表于 2025-3-28 05:47:22 | 只看該作者
Fei Zheng,Qingguo Xu,Zhou Lei,Huaikou Miao constructed with a set of statistical image features extracted at various scales. The experimental results show that, the Random Forest classification approach with multiscale features achieved higher accuracy than J48 decision tree based medical image classification.
39#
發(fā)表于 2025-3-28 09:32:10 | 只看該作者
40#
發(fā)表于 2025-3-28 12:55:52 | 只看該作者
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