目前共计 511 个标签
1/t衰减/1/t decay 2FA ACNet AML(approximate max-pooling localization) AdaGrad Adam AlexNet Angular Loss AutoAugment Baidu Boost Graph Library/BGL C3D CNN宏架构/CNN macroarchitecture CNN微架构/CNN microarchitecture ChatGPT ChatGPT for Google Chrome 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 Github GoogLeNet Google Google Code Style Google Test Google landmark dataset (GLD) v1 Google landmark dataset (GLD) v2 Gradio 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 MA 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 PETA 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 RAP 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 YOLO9000 YOLOv1 YOLOv2 YOLOv3 YOLOv5 YOLOv8 ZFNet albumentation attention transfer/注意力迁移 c++ canny chevereto cifar10 cifar100 clang-format clion coco cocoapi coding csdn dali darknet19 darknet53 detectron2 docker docker-compose f1 score fashion mnist fcn-resnet101 flask flops fps git git-flow gitea gitee github github-flow gitlab gitlab-flow graphviz hexo hsv/hue saturation value/色调 饱和度 明度 im2col im2row imagenet iris jenkins jetbrains jupyter notebook k-means cluster/k-means聚类 kthreaddi k近邻/k-nearest neighbor/KNN lab labelimg labelme laplacian leaky relu letterbox linux lmdb logo.svg logoly mAP/mean average precision matplotlib mkdocs mnist mpdataset next nextcloud nginx nms/non-maximum-suppression/非最大抑制 nodejs nomachine numpy nvidia onnx onnxruntime opencv oxford5k pandas paris6k pascal voc peek portainer.io prefetcher pycharm pytest python pytorch pytorchviz readme relu relu6 resnet resnet50 rgb/red green blue/红色 绿色 蓝色 scharr sigmoid sis skimage sklearn sobel softmax回归/softmax regression sphinx ssh tanh tensorboard tensorrt thop tomcat torchsummary torchvision travis ci trtexec ubuntu vino warmup web xmltodict yolov5 yolov8 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 场景分析/scene analysis 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 多标签分类/multi-label classification 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 帧间差分/inter-frame difference 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 梯度加权类激活映射/Gradient-weighted Class Activation Mapping 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 深度学习/deeplearning 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 类激活映射/Class Activation Mapping 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 行人属性识别/pedestrian attribute recognition 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