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The defect detection of industrial parts is realized by combining VGg and residual network. Based on keras and tensorflow, it can be used directly
Update : 2024-06-03 Size : 13kb Publisher : xiaozhanggao

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Using MATLAB to realize license plate classification, including location, segmentation and character recognition. The recognition method is neural network.
Update : 2024-06-03 Size : 6kb Publisher : 左手拿鸡腿

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It gives the source code and explanation of MOPSO algorithm, and gives the test function
Update : 2024-06-03 Size : 426kb Publisher : 可爱小梦鱼

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175/5000 This routine is a small project that I did in the graduate stage. The project uses pytorch's deep learning framework to recognize human body posture, and can realize skeleton recognition of head and body! In the
Update : 2024-06-03 Size : 2.98mb Publisher : linmi

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LSTM used for stock forecasting, good effect, welcome to download, hope to be satisfied
Update : 2024-06-03 Size : 1.16mb Publisher : ladka

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This is a source code about wnn. The code is coding by matlab 2016a and it can apply to predict someting based on time series.
Update : 2024-06-03 Size : 1kb Publisher : 宏远伟大

Based on neural network Load Forecasting
Update : 2024-06-03 Size : 7kb Publisher : wu——yi

sm3_rst_n, csm2_rst_n, csm1_rst_n, csm0_rst_n, b_10gf_rst_n, f_10gf_rst_n, b_ge_rst_n, f_ge_rst_n, mucus_rst_n, daughter_rst_n, csm0_led_n, csm1_led_n, csm2_led_n, csm3_led_n, hdd_cf_led_n, in_out_irq_n, csm_run_irq_n,
Update : 2024-06-03 Size : 6.82mb Publisher : liang1234!!!

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ANFIS (Adaptive-Network-based Fuzzy Inference System) is a fuzzy inference systemimplemented in the framework of adaptive networks, and it can construct an input-output mapping based on both human knowledge (in the form
Update : 2024-06-03 Size : 604kb Publisher : 西门吹雪

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Lenet5 is composed of seven layers of CNN
Update : 2024-06-03 Size : 501kb Publisher : 659+59

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algorithm for path planning
Update : 2024-06-03 Size : 6kb Publisher : Acacius

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模拟退火算法解决TSP路径规划问题,内容很详细,可以供初学者详细学习,可以运行成功
Update : 2020-03-28 Size : 183.13kb Publisher : 646137382@qq.com
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