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Hi everyone,
This is achieved by trading an acceptable amount of accuracy, making the network approximately 70 times faster than Tiny-YOLO.Greater inference speed-ups were also achieved on a desktop
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Asking here because issue tracking is disabled in the other project: I'd like to use [yolo2_light](https://github.com/AlexeyAB/yolo2_light) for a robotics research project because it's more light-weig…
tlind updated
5 years ago
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Thanks for your nice work. I load the pre-train model and get the 78.6% acc on A->W. But I'm a little confused about the Softmax function in your code.
As the input is N*C, why the Softmax function …
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I 've found this article and I am impressed with the FPS and high accuracy they announce.
https://www.xailient.com/post/challenges-of-running-deep-learning-computer-vision-on-computationally-limite…
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Hello guys, as you know tensorflow has several methods for model quantization after finish training in order to reduce size with a bit of accuracy trade off. I am wondering is there any similar featur…
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I haven’t found the ADQ method related code in the project. Haven’t I uploaded it yet?
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I could only see regular convolutional layer (tf.nn.conv2d) applied on binary inputs and weights. Where can I find code of fast binary convolution using xnor ?
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## Quantization Method for conv, deconv and fc Layers.
Here I want to implement the quanzization on operation in conv, deconv and fc layers. Much quantization method are included in this paper: Ristr…
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valgrind --tool=memcheck --leak-check=full --show-reachable=yes --trace-children=yes ./darknet classifier valid squeezenet/imagenet1k.data squeezenet/squeezenet.cfg squeezenet/squeezeNetCaffe.weight…
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https://blog.csdn.net/qianqing13579/article/details/71076261
LeNet论文的翻译与CNN三大核心思想的解读
https://blog.csdn.net/silent56_th/article/details/53428057
LeNet论文阅读:CNN设计原理