YOLO-V3

06-26

BigGAN

06-20

pix2pix

06-14

DiscoGAN

06-12

CycleGAN

06-11

SRGAN

06-09

WGAN-GP

06-07

WGAN

06-05

LSGAN

06-04

COGAN

06-03

ACGAN

06-01

CGAN

05-31

DCGAN

05-29

GAN

05-27

生成式对抗网络数据集

05-25

熵，交叉熵，相对熵的关系

05-24

Regularization黑科技

05-23

TensorFlow训练，验证，预测的三种方法

05-22

TensorFlow定义网络层

05-21

TensorFlow定义模型的三种方法

05-20

误差，偏差，方差，噪声的关系

05-19

Callbacks黑科技

05-18

Transfer learning(迁移学习)

05-17

TensorBoard黑科技

05-14

Data Augmentation(数据增强)

05-13

Metrics黑科技

05-12

Learning Rate黑科技

05-11

Optimizer黑科技

05-10

Loss黑科技

05-09

Addition VS Concatenate

05-08

Normalization黑科技

05-07

Upsampling黑科技

05-06

SSD

05-05

Convolution黑科技

05-04

Activation黑科技

05-02

目标检测数据集

04-30

DeepLab-V3+

04-27

PSPNet

04-24

UNet

04-21

SegNet

04-18

语义分割数据集

04-15

GhostNet

04-08

ShuffleNet-V2

04-02

EfficientNet

03-31

EffNet

03-28

MobileNet-V3

03-26

MobileNet-V2

03-22

MobileNet

03-20

SqueezeNet

03-18

SENet

03-17

DenseNet

03-16

Xception

03-14

ResNeXt

03-13

Inception-ResNet-V2

03-12

Inception-V3

03-10

ResNet

03-09

VGG

03-08

Dynamic & Static(动态图与静态图)

10-28

PyTorch

09-08

TensorFlow

09-06