Table 2. Experimental results of different SE-ResNet architectures on Cifar.

Method	Module	Cifar-10			Cifar-100
		#params	#model size	Accuracy	#params	#model size	Accuracy
SE-ResNet-18	basic	11, 272K	90.4Mb	94.85 ± 0.14	11, 312K	90.8Mb	75.86 ± 0.22
SE-ResNet-26	bottleneck	15, 383K	123.4Mb	93.90 ± 0.18	15, 567K	124.8Mb	75.40 ± 0.27
SE-ResNet-34	small	8, 145K	65.6Mb	94.79 ± 0.17	8, 191K	65.9Mb	75.81 ± 0.13
SE-ResNet-50	bottleneck	26, 100K	209.4Mb	94.67 ± 0.09	26, 285K	210.8Mb	78.02 ± 0.25
SE-ResNet-66	small	14, 986K	120.7Mb	95.26 ± 0.18	15, 033K	121.1Mb	77.02 ± 0.20
BHCNet-3	small	198K	2.1Mb	92.30 ± 0.14	204K	2.2Mb	68.36 ± 0.23
BHCNet-6	small	401K	4.2Mb	93.18 ± 0.14	407K	4.2Mb	70.33 ± 0.25