Comments (3)
- 我们在文中提到,调整通道数控制FLOPs。需要调整通道数将FLOPs与之前工作对齐从而公平对比,与NAS无关。
- 同理,需要控制FLOPs公平对比,2^n通道数与精度无关。
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我可以理解为论文表 5 中的那种通道数设计和精度并没有关系吧,从而我把 shufflenetv2 作为目标检测的 backbone,可以对通道数进行修改为 2^n,这是不会影响 backbone 本身的精度.
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精度与FLOPs有关,与是否为2^n无关
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Related Issues (20)
- What is the training setting for reproducing ShuffleNetV2+? HOT 1
- network HOT 1
- Pretrained model HOT 2
- Traceback and AssertionError in train HOT 4
- question on why 4 fragments in parallel runs slower than 4 fragments in series HOT 2
- 原则2中为什么 MAC 与组数 g 成正比的问题 HOT 2
- channel shuffle layer's location HOT 1
- Low accuracy on multi-clsss problem HOT 1
- training speed HOT 3
- adjust_bn_momentum的问题? HOT 4
- A mismatch in shufflenetv1 about ReLU HOT 6
- Question about Fig.2 HOT 1
- why need 'LastSE' HOT 1
- the code implementation for Shuffle Unit is inconsistent with the paper HOT 1
- Weight file decompressed shows corruption
- 关于ShuffleNetV1模型中 model_size 和 stage_repeat的问题
- channel shuffle HOT 3
- 我在用shufflenetv1作为yolov7的骨干网络,可是训练的时候数据格式正常,但。。。。
- Replace SE with SA layer?
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