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- || 神经网络 (Neural Networks) || 趋势跟踪、模式识别 || 强大的非线性建模能力,能够� || 循环神经网络 (Recurrent Neural Networks) || 时间序列预测 || 能够处理时间序列数据,捕捉时间依� ...8 KB (123 words) - 19:20, 11 April 2025
- * **卷积神经网络 (Convolutional Neural Networks - CNNs):** CNNs 特别擅长处理图像数据,它们能够自动学习� * **生成对抗网络 (Generative Adversarial Networks - GANs):** GANs 由两个神经网络组成:一个生成器和一个判� ...8 KB (151 words) - 18:01, 6 May 2025
- * **神经网络 (Neural Networks)**: 模仿人脑神经元结构的数学模型,是深度学习的基础� * **卷积神经网络 (Convolutional Neural Networks - CNN)**: 专门用于处理图像和视频数据的神经网络。 ...9 KB (173 words) - 06:36, 18 May 2025
- ...g, et al. "Efficientnet: Rethinking model scaling for convolutional neural networks." *Proceedings of the international conference on machine learning*. PMLR, [[Category:卷积神经网络 (Convolutional neural networks)]] ...10 KB (173 words) - 13:40, 7 May 2025
- 超分辨率卷积神经网络 (Super-Resolution Convolutional Neural Network, SRCNN) 是一种深度学习方法,用于图像超分辨率重� * **FSRCNN (Fast Super-Resolution Convolutional Neural Network):** FSRCNN 在 SRCNN 的基础上进行了改进,通过在提� ...9 KB (176 words) - 19:40, 7 May 2025
- ...积神经网络]] (Convolutional Neural Networks, CNN) 和[[循环神经网络]] (Recurrent Neural Networks, RNN) 领域的进展,使得人工智能在图像识别、语音识别和 ...10 KB (108 words) - 05:01, 18 May 2025
- * **深度特征 (Deep Features):** 随着[[深度学习]]的兴起,基于[[卷积神经网络 (Convolutional Neural Networks, CNNs)]]提取的深度特征成为了主流方法。这些特征通过多� * **CNNs (Convolutional Neural Networks):** CNNs 通过多层卷积和池化操作自动学习图像特征,可� ...9 KB (139 words) - 14:21, 18 May 2025
- ## 生成对抗网络 (Generative Adversarial Networks) 初学者指南 * **Deep Convolutional GANs (DCGANs):** DCGANs 使用卷积神经网络 (CNNs) 作为生成器和 ...9 KB (186 words) - 15:12, 7 May 2025
- # Neural Networks * **前馈神经网络 (Feedforward Neural Network):** 信息单向流动,从输入层到输出层,没有反馈回 ...9 KB (104 words) - 05:20, 8 May 2025
- ...' (Convolutional Neural Networks, [[CNN]]) 和'''循环神经网络''' (Recurrent Neural Networks, [[RNN]]) 的应用,语音识别的准确率和鲁棒性得到了进一� ...10 KB (287 words) - 04:17, 18 May 2025
- * **卷积神经网络 (Convolutional Neural Networks - CNNs):** [[卷积神经网络]]是深度学习中最常用的网络结构 ...11 KB (126 words) - 04:15, 18 May 2025
- ...ning):** 一种特殊的机器学习方法,使用多层神经网络来学习复杂的特征表示。 [[卷积神经网络]] (Convolutional Neural Networks, CNNs) 是深度学习在计算机视觉领域最常用的模型。 ...10 KB (182 words) - 11:22, 2 May 2025
- ...究人员提出了基于深度学习的图像超分辨率方法。早期的深度学习方法,如[[SRCNN]] (Super-Resolution Convolutional Neural Network),虽然取得了比传统方法更好的效果,但生成的图� [[Category:生成对抗网络 (Generative Adversarial Networks)]] ...9 KB (113 words) - 02:31, 11 May 2025
- 传统的GAN,例如 [[DCGAN]] (Deep Convolutional Generative Adversarial Network),的判别器通常会对整个图像进� ...成器负责从随机噪声中生成图像。常用的生成器架构包括 [[卷积神经网络]] (CNN) 和 [[转置卷积神经网络]] (Deconvolutional Neural Network)。 ...9 KB (185 words) - 05:17, 9 May 2025
- * [[神经网络 (Neural Networks)]]:展示如何使用 PyTorch 构建和训练神经网络。 * **卷积神经网络 (Convolutional Neural Networks):** 用于图像识别和处理的神经网络。 ...10 KB (326 words) - 16:21, 9 May 2025
- [[Category:卷积神经网络 (Convolutional neural networks)]] ...8 KB (146 words) - 16:05, 4 May 2025
- [[Category:卷积神经网络 (Convolutional neural networks)]] ...9 KB (151 words) - 13:10, 6 May 2025
- * '''卷积层 (Convolutional Layers):''' 这是 VGGNet 的核心组成部分。它使用一系列小的 [[Category:卷积神经网络 (Convolutional Neural Networks)]] [[技术分析]] [[数据增强]] [[ReLU]] [[最大池化]] [[Softmax � ...10 KB (264 words) - 16:48, 12 May 2025
- ...Networks (CNNs), Recurrent Neural Networks (RNNs), and Feedforward Neural Networks. ...pport:''' CNTK offers APIs in [[Python]], [[C++]], and [[CNML]] (Cognitive Neural Network Language), providing flexibility for developers with different skil ...10 KB (1,202 words) - 11:29, 7 May 2025
- [[AI Generative Adversarial Networks (GANs)]] [[AI Recurrent Neural Networks (RNNs)]] ...30 KB (2,688 words) - 03:00, 7 May 2025