大海

从今天起,做一个幸福的人

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目前共计 467 个标签
1/t衰减/1/t decay ACNet AML(approximate max-pooling localization) AdaGrad Adam AlexNet Angular Loss AutoAugment Boost Graph Library/BGL C3D CNN宏架构/CNN macroarchitecture CNN微架构/CNN microarchitecture Close-set/闭集 ConvNeXt CroW/cross-dimensional weighting and pooling Cutmix DBSCAN/the density-based spatial clustering of applications with noise DVC Database-side augmentation/DBA/数据端增强 DenseNet EMA/Exponential Moving Average/指数滑动平均 EfficientNet EfficientNet-lite EfficientNetV2 FSP Matrix FaceNet Fast AutoAugment Fast R-CNN Faster R-CNN FitNets Focal Loss Fuzed-MBconv GELU/Gaussian Error Linear Unit GeM/generalized-mean/广义平均池化 General Pair Weighting/GPW/通用成对加权 GhostNet GoogLeNet Google Code Style Google Test Google landmark dataset (GLD) v1 Google landmark dataset (GLD) v2 HMDB Inception Inception-ResNet Inverted Bottleneck Jacobian矩阵/Jacobian matrix Jetson AGX Xavier KR/knowledge review/知识复习 Kinetics L2归一化/L2-Normalize LN/Layer Normalization LeNet-5 Listwise loss MAC/maximum activations of convolutions Mixup MnasNet MobileNet Multi-similarity loss/MS loss/多重相似性损失 MultiGrain N-pair Loss NIN/Network In Network Nesterov加速梯度/nesterov's accelerated gradient/NAG Netscope CNN Analyzer Network Slimming Non-local OFD OKR/Objectives and Key Results/目标与关键结果 Open-set/开集 OpenDVC Overhaul PCA whitening/PCA白化 PCA whitening/PCA白化 PPM/Portable Pixel Map/便携式像素地图 PR曲线/PR curve/精确-召回曲线/precise-recall curve Penn-Fudan Progressive learning/渐近式学习 PyRetri R-CNN/regions with CNN features/具有CNN特征的区域 R-MAC/regional maximum activation of convolutions RA/Repeated Augment/重复采样 RFD RKNN RMSProp ROC曲线/ROC curve/受试者工作特征曲线/receiver operating characteristic curve RPN/region proposal network/区域建议网络 RandAugment Rank loss/排序损失 ResNeSt ResNet ResNetXt ResVGG RetinaNet RoI Pooling SENet/squeeze-and-excitation network SKNet/selective kernel network SPP-net SPoC descriptors/SPoC描述符 SSD/single shot multibox detector SSDLite STL ShuffleNet SlowFast Split-Attention Networks SqueezeNet Swin Transformer T3D TRN/temporal relation network TSM/temporal shift module TSN/temporal segment network TinyNet UCF101 VGGNet Vision Transformer X3D YOLO/you only look once ZFNet albumentation attention transfer/注意力迁移 c++ canny chevereto cifar10 cifar100 clang-format coco cocoapi coding csdn dali detectron2 docker docker-compose f1 score fashion mnist flask flops fps git git-flow gitee github github-flow gitlab gitlab-flow graphviz hexo hsv/hue saturation value/色调 饱和度 明度 im2col im2row iris jenkins jupyter notebook k-means cluster/k-means聚类 kthreaddi k近邻/k-nearest neighbor/KNN lab labelimg labelme laplacian leaky relu linux lmdb logo.svg logoly mAP/mean average precision matplotlib mkdocs mnist mpdataset next nextcloud nginx nodejs nomachine numpy nvidia opencv oxford5k pandas paris6k pascal voc peek prefetcher pycharm pytest python pytorch pytorchviz readme relu relu6 rgb/red green blue/红色 绿色 蓝色 scharr sigmoid sis skimage sklearn sobel softmax回归/softmax regression sphinx tanh tensorboard thop tomcat torchsummary torchvision travis ci ubuntu vino warmup xmltodict yuv zlogo 三元组损失/triplet loss 中心差分公式/the centered difference formula 中心极限定理/central limit theorem 主成分分析/princial component analysis/PCA 二进制哈希码/binary hash code 交叉熵损失/cross entropy loss 交叉验证/cross validation 交集并集比/intersection over union/IoU 代价函数/cost function 代数运算algebraic operation 伯努利分布/bernoulli distribution 余弦退火/cosine annealing 信息检索/information retrieval 假阳性/false positive/FP 假阳性率/false positive rate//FPR/误报率/probability of false alarm 假阴性/false negative/FN 偏导数/partial derivative 充分条件/sufficiency 克鲁斯卡尔算法/kruscal algorithm 全局平均池化层/global average pooling layer/GAP 全局最小值/global minimum 全微分/total differential 全连接层/fully connected layer/FC 共扼/conjugate 内积/inner product 内部协变量偏移/internal covariate shift 决策树/decision tree 决策边界/decision boundary 几何运算/geometric operations 凸函数/convex function 分层深度搜索/hierarchical deep search 分辨率乘法器/resolution multiplier 前端开发/frontend development 动量/momentum 协方差/covariance 协方差矩阵/covariance matrix 单位化/unitization/规范化/normalization/标准化/standardization 单元测试/unit testing/UT 卷积/convolution 卷积层/convolutional layer 卷积神经网络/convolutional neural network/CNN 参数共享/parameter sharing 双流网络/two-stream network 反卷积网络/deconvolutional network/deconvnet 反向传播/backpropagatation 反向残差块/inverted residuals block 反池化/unpool 合理性检查/sanity check 后端开发/backend development 向量/矢量/vector 向量压缩/product quantization 周期性学习率/cyclical learning rates 图/graph 图像定位数据集/image localization dataset 图的遍历/traversing graph 均值平均精度/mean average precision/mAP 均匀分布/uniform distribution/矩形分布 均方误差/mean square error/MSE 均方误差/mean squared error/MSE 域名/domain 基于内容的图像检索/content-based image retrieval 基于图的图像分割 备案 多层感知器/multilayer perceptron/MLP 多裁剪评估/multi-crop evaluation 学习率/learning rate 学习率退火/annealing the learning rate 完全图/complete graph 实例检索/instance retrieval 客户端开发/client development 宽度乘法器/width multiplier 密集评估/dense evaluation 导数/derivative 局部响应归一化/local response normalization/LRN 局部最小值/local minima 局部连接/local connection 层剪枝/layer pruning 工作流/workflow 平均数/mean 平均精度/average precision/AP 并查集/disjoint set/union-find set/merge-find set 广度优先遍历/breadth first search/BFS 度/degree 度量学习/metric learning 微分/differential 微调/finetuning 德国信用卡数据/german credit data 徽章/badge 必要条件/necessity 总体方差/population variance 感受野/receptive field 成绩函数/score function 截断SVD/truncated SVD 批量大小/batch size 批量归一化/batch normalization/BN 折页损失/hinge loss 持续发布/continuous release 持续部署/continuous deploy 持续集成/continuous integration 指数衰减/exponential decay 按大小合并/union by size 按秩合并/union by rank 损失函数/loss function 提前停止策略/early stopping 支持向量机/support vector machine/SVM 敏捷开发/agile development 数值梯度/numerical gradient 数学公式/mathematical formula 数学期望/mathematical expectation/均值/expected value 数据加载器/dataloader 数据扩充/data augmentation 数据损失/data loss 数据端特征增强/database-side feature augmentation 方向导数/directional derivative 方向梯度直方图/histogram of oriented gradients/HOG 方差/variance 无向图/undirected graph 无向边/undirected edge 普里姆算法/prim algorithm 曲线下面积/area under curve/AUC 最大值上限/max-upper constraint 最小二乘法/least square method 最小生成树/minimum spanning tree/MST 有向图/directed graph 有向边/directed edge 服务器端开发/server-side development 权重初始化/weight Initialization 权重剪枝/weight pruning 权重惩罚/weight penalty 权重衰减/weight decay 查全率/召回率/recall/敏感度/sensitivity/真阳性率/true positive rate/TPR 查准率/精确率/precision/正预测值/positive predictive value/PPV 查询扩展/query expansion/QE 标准化/standardization/规范化/归一化/normalization 标准差/standard deviation 标投影/scalar projection 标签平滑正则化/label smoothing regularization/LSR 标量/scalar 样本方差/sample variance 梯度/gradient 梯度下降/gradient descent 梯度检查/gradient check 梯度消失/gradient vanishing 梯度爆炸/gradient exploding 梯度矩阵/gradient matrix 概率论/probability theory 模型集成/model ensemble 欠拟合/underfitting 正交基/orthogonal basis 正则化/regularization 正则化损失/regularization loss 正态分布/常态分布/normal distribution/高斯分布/gaussian distribution 正样本/阳性样本/positive case 正确率/准确率/accuracy 池化层/pooling layer 泰勒公式/taylor formula 测试驱动开发/test-driven development/TDD 深度优先遍历/depth first search/DFS 深度压缩/deep compression 混合图/mixed graph 混淆矩阵/confusion matrix 温度缩放/temperature scaling 漏检率/false discovery rate/FDR 激活函数/activate function 瀑布模型/waterfall model 点积/dot product 特征向量/eigen vector 特征金字塔网络/Feature Pyramid Network/FPN 独立同分布/independent and identically distributed 独立性/independence 瓶颈残差块/bottleneck residual block 生成树/spanning tree 白化/whitening 目标函数/objective function 目标分割/object segmentation 目标检测/object detection 直方图/histogram 直方图均衡/histogram equalization 相关/correlation 相关性/correlation 真阳性/true positive/TP 真阴性/true negative/TN 矢投影/vector projection 知识蒸馏/knowledge distillation 矩阵/matrix 神经元/neuron 神经网络/neural network 移动端开发/mobile development 稀疏图/sparse graph 稠密图/dense graph 空间金字塔池化/spatial pyramid pooling 纹理特征/texture features 线性变换/linear transformation 线性回归/linear regression 线性无关/linear independence 线性映射/linear mapping 线性瓶颈层/linear bottleneck layer 线性相关/linear correlation 线性缩放规则/linear scaling rule 经验风险/empirical risk 结构化剪枝/structured pruning 结构化稀疏学习/Structured Sparsity Learning/SSL 结构风险/structural risk 网格搜索/grid search 网络退化/network degradation 腾讯云 自适应平均池化层/adaptive average pool layer 范数/norm 螺旋模型/spiral model 解构和构造学习/Destruction and Construction Learning/DCL 解析梯度/analytic gradient 训练量化/trained quantization 贝叶斯优化/bayesian optimization 负对数似然代价函数/negative log likelihood cost function 负样本/阴性样本/nevative case 超参数优化/hyperparameter optimization 超平面/hyperplane 路径减半/path halving 路径压缩/path compression 转置/transposition 边界损失/Margin Loss 边界框回归/boundary box regression 边缘检测/edge detection 迁移学习/transfer learning 过拟合/overfitting 连通分量/connected component 连通图/connected graph 迭代模型/iterative model 迹/trace 选择性搜索/selective search/ss 逐元素自适应学习率方法/per-parameter adaptive learning rate methods 逐点分组卷积/pointwise group convolution 逐通道可分离卷积/深度可分离卷积/depthwise separable convolution 通道剪枝/channel pruning 通道重排/channel shuffle 逻辑回归/logistic regression/LR 邻接矩阵/adjacency matrix 邻接表/adjacency list 重叠池化/overlapping pool 链式法则/chain rule 错误率/error rate 锚点/anchor 阿里云 随机失活/random dropout 随机搜索/random search 随步数衰减/step decay 难负例挖掘/hard negative mining 非对称卷积块/asymmetric convolution block/ACB 非对称卷积网络/asymmetric convolutional network/ACN 非最大值抑制/non-maximum suppression/NMS 颜色空间/color space/颜色模型/color model 高斯噪声/gaussian noise 高斯导数直方图/gaussian derivative histogram 高斯滤波/gaussian filter/高斯模糊/gaussian blur