文件名称:darknet
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Text]
- 上传时间：
- 2017-02-14
- 文件大小：
- 2.05mb
- 下载次数：
- 0次
- 提 供 者：
- 安*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
神经网络引入后，检测框架变得更快更准确。然而，大多数检测方法受限于少量物体。检测和训练数据上联合训练物体检测器，用有标签的检测图像来学习精确定位，同时用分类图像来增加词汇和鲁棒性。原YOLO系统上生成YOLOv2检测器；在ImageNet中超过9000类的数据和COCO的检测数据上，合并数据集和联合训练YOLO9-After the neural network is introduced, it is becoming faster and more accurate detection fr a me. However, most detection methods is limited by the small number of objects. Testing and training on joint training data object detector for detecting an image tag to learn precise positioning, while using image classification to increase vocabulary and robustness. YOLOv2 detector generates the original YOLO system ImageNet more than in the 9000 class of data and test data COCO, the consolidated data sets and joint training YOLO9000
(系统自动生成,下载前可以参看下载内容)
下载文件列表
LICENSE
Makefile
cfg
...\alexnet.cfg
...\cifar.cfg
...\cifar.test.cfg
...\coco.data
...\combine9k.data
...\darknet.cfg
...\darknet19.cfg
...\darknet19_448.cfg
...\extraction.cfg
...\extraction.conv.cfg
...\extraction22k.cfg
...\go.test.cfg
...\gru.cfg
...\imagenet1k.data
...\imagenet22k.dataset
...\jnet-conv.cfg
...\msr_152.cfg
...\msr_34.cfg
...\msr_50.cfg
...\rnn.cfg
...\rnn.train.cfg
...\strided.cfg
...\t1.test.cfg
...\tiny-yolo-voc.cfg
...\tiny-yolo.cfg
...\tiny.cfg
...\vgg-16.cfg
...\vgg-conv.cfg
...\voc.data
...\writing.cfg
...\yolo-voc.cfg
...\yolo.cfg
...\yolo9000.cfg
...\yolov1
...\......\tiny-coco.cfg
...\......\tiny-yolo.cfg
...\......\xyolo.test.cfg
...\......\yolo-coco.cfg
...\......\yolo-small.cfg
...\......\yolo.cfg
...\......\yolo.train.cfg
...\......\yolo2.cfg
data
....\9k.labels
....\9k.names
....\9k.tree
....\coco.names
....\coco9k.map
....\dog.jpg
....\eagle.jpg
....\giraffe.jpg
....\goal.txt
....\horses.jpg
....\imagenet.labels.list
....\imagenet.shortnames.list
....\inet9k.map
....\labels
....\......\100_0.png
....\......\100_1.png
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....\......\102_0.png
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....\......\104_0.png
....\......\104_1.png
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....\......\104_5.png
....\......\104_6.png
....\......\104_7.png