A Convolutional Neural Network (CNN), also known as ConvNet, is a specialized type of deep learning algorithm mainly designed for tasks that necessitate object recognition, including image classification, detection, and segmentation. CNNs are employed in a variety of practical scenarios, such as aut...
5.5 Deep convnets along with transfer learning strategy 论文:(2015) Automatic age estimation based on deep learning algorithm 简述:Dong等人使用最广泛使用的“Images of Groups of people”数据集,使用深层CNN和迁移学习的概念进行年龄估计。以错误率、精确匹配正确率(AEM)、年龄类别误差(AEO)和混淆矩阵作为评价...
4.5 价值迭代算法(Value iteration algorithm) 算法包含2步: 第一步,初始化价值:V0(s)=0 第二步,基于之前的价值进行迭代: 4.6 最大似然估计(Maximum likelihood estimate) 状态转移概率的最大似然估计如下:Psa(s′)=状态s到s′行为a的次数状态s的行为次数 ...
Teh, “A fast learning algorithm for deep belief nets,” Neural Comput., vol. 18, no. 7, pp. 1527–1554, 2006.[83] Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle, “Greedy Layer-Wise Training of Deep Networks,” in Advances in Neural Information Processing Systems 19, no...
This means that if you include a large stride in the convolution filter, you are changing the types of features you extract in the algorithm, whereas if you change it in the pooling layer, you are simply changing how much the data is downsampled. ...
第二点,Deep Learning强大的地方就是可以利用网络中间某一层的输出当做是数据的另一种表达,从而可以将其认为是经过网络学习到的特征。基于该特征,可以进行进一步的相似度比较等。 第三点,Deep Learning算法能够有效的关键其实是大规模的数据,这一点原因在于每个DL都有众多的参数,少量数据无法将参数训练充分。
How to Research a Machine Learning Algorithm(http://machinelearningmastery.com/how-to-research-a-machine-learning-algorithm/) Google Scholar(http://scholar.google.com/) 3) 重采样方法 你必须知道你的模型效果如何。你对模型性能的估计可靠吗?
YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers https://arxiv.org/abs/1811.05588 AttentionNet: Aggregating Weak Directions for Accurate Object Detection intro: ICCV 2015 intro: state-of-the-art performance of 65% (AP) on PASCAL VOC 2007/2012 human detection ...
Multi‑step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network‑Long Short‑Term Memory (CNN‑LSTM) model enhanced by Boruta‑XGBoost feature selection algorithm 方法:论文使用现代深度学习技术开发了一个基于CNN-LSTM框架的预测模型,用于预测河流中的电...
We will continue to optimize the ARM platform according to the online and offline communication with ARM related algorithm team. NEON usage covers all aspects of convolution, normalization, pooling, and so on. Assembly optimizations are optimized for register assembler operations. Loop unrolling, to ...