Image Classification on ImageCLEF-DA benchmark leaderboard · SOTA2 Research

Image Classification on ImageCLEF-DA

81Accuracy (I -> P)ETD

Evaluation Results

Method	Links
ETD2021.07		81	91.7	97.9	93.3	79.5	95	89.7
DMP2021.07		80.7	92.5	97.2	90.5	77.7	96.2	89.1
CKB2021.07		80.7	93.7	97	93.5	79.2	97	90.2
CKB+MMD2021.07		80.7	92.2	96.5	92.2	79.9	96.7	89.7
MDDA2019.09		79.8	91.5	95.7	92	78.8	95.5	88.9
MEDM2020.02		78.5	93	98.1	92.8	77.2	95.5	88.9
CDAN2019.09		78.3	91.2	96.7	91.2	77.2	93.7	88.1
CAN2019.09		78.2	87.5	94.2	89.5	75.8	89.2	85.7
DDAN2019.09		78	91	94	91	76	92.7	87.2
CDAN2020.02		77.7	90.7	97.7	91.3	74.2	94.3	87.7
CDAN+E2021.07		77.7	90.7	97.7	91.3	74.2	94.3	87.7
TCA2019.09		77.5	80.8	93.2	89.3	74.5	83.7	83.2
JAN2016.05		76.8	88	94.7	89.5	74.2	91.7	85.8
SVM2019.09		76.8	80.2	91.2	86	73.2	85.8	82.2
JAN2019.09		76.8	88	94.7	89.5	74.2	91.7	85.8
KGOT2021.07		76.3	83.3	93.5	87.5	74.8	89	84.1
RTN2020.02		75.6	86.8	95.3	86.9	72.7	92.2	84.9
GFK2019.09		75.5	78	93	86.3	73.3	82.3	81.4
JDA2019.09		75.3	77.8	94	90.8	73.6	83.5	82.5
DANN2019.09		75	86	96.2	87	74.3	91.5	85
DAN2020.02		75	86.2	93.3	84.1	69.8	91.3	83.3
RevGrad2020.02		75	86	96.2	87	74.3	91.5	85
MADA2020.02		75	87.9	96	88.8	75.2	92.2	85.8
DANN2021.07		75	86	96.2	87	74.3	91.5	85
ResNet2016.05		74.8	83.9	91.5	78	65.5	91.2	80.7
ResNet2019.09		74.8	83.9	91.5	78	65.5	91.2	80.7
1NN2019.09		74.8	74	89	83.5	71.3	76.2	78.1
Source2021.07		74.8	83.9	91.5	78	65.5	91.2	80.7
RTN2016.05		74.6	85.8	94.3	85.9	71.7	91.2	83.9
DAN2016.05		74.5	82.2	92.8	86.3	69.2	89.8	82.5
DAN2019.09		74.5	82.2	92.8	86.3	69.2	89.8	82.5
DAN2021.07		74.5	82.2	92.8	86.3	69.2	89.8	82.5
CORAL2019.09		73.7	71.3	88.7	83	71.5	72	76.7
RTN2016.05		67.4	81.3	89.5	78	62	89.1	77.9
DAN2016.05		67.3	80.5	87.7	76	61.6	88.4	76.9
JAN2016.05		67.2	82.8	91.3	80	63.5	91	79.3
AlexNet2016.05		66.2	70	84.3	71.3	59.3	84.5	73.9