## 3 Experimental Results and Analysis
### Experimental Results
#### 3.4.1 Results of the Basic Experiments  
As shown in Table 1, all experimental indexes of our proposed CABIR model are superior to the four baseline models for comparison over the RSICD dataset. Among the four baseline models, AMFMN [18] has the top overall performance. However, our CABIR is 10.3% higher than it in the index mR, representing the balancing performance of a model, and the index R@SUM, representing the overall performance. The top-performing baseline model in the index R@1 for text retrieval is SCAN [27]. Yet, we have raised it by 46.8% in our model. Given the higher difficulty of the RSICD dataset, the optimal results achieved over this dataset by us relative to the baseline models are undoubtedly stronger evidence of the validity of the method. As shown in Table 2, our CABIR model has achieved optimal performance in the five experimental indexes over the UCM-Captions dataset. For a limited number of indexes haven't reached their best performance, such as R@1 in text retrieval, they can still reach satisfactory accuracy and show a very tiny gap when compared with the top-performing baseline model. Moreover, the indexes mR and R@SUM of our model are significantly higher than their counterparts in all baseline models, with a rise of 5.7%. Particularly, the index R@10 in image retrieval achieves an extremely high level, with a rise of 12.3% as compared to the top-performing baseline model AMFMN [18]. As shown in Table 3, our CABIR model achieves the optimal results in the six experimental indexes over the Sydney-Captions dataset. Specifically, the nonoptimal indexes R@5 and R@10 in image retrieval are only second to the optimal index by 4.1%. In the indexes mR and R@SUM, our model achieves a rise of 7.3% as compared to the top-performing baseline model AMFMN [18]. The best result is associated with the index R@5 in text retrieval and is significantly higher than those of the four baseline models, with a rise of 11.8% as compared to the top performer. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**RSICD Dataset**} \\ \hline \multirow{2}{*}{**Method**} & \multicolumn{3}{c}{**Text Retrieval**} & \multicolumn{6}{c}{**Image Retrieval**} \\  & **R@1** & **R@5** & **R@10** & **R@1** & **R@5** & **R@10** & **mR** & **R@sum** \\ \hline VSE++ & 3.38 & 9.51 & 17.46 & 2.82 & 11.32 & 18.1 & 10.43 & 62.59 \\ SCAN t2i & 4.39 & 10.9 & 17.64 & 3.91 & 16.2 & 26.49 & 13.25 & 79.53 \\ SCAN t2t & 5.85 & 12.89 & 19.84 & 3.71 & 16.4 & 26.73 & 14.23 & 85.42 \\ MFTN & 5.02 & 12.52 & 19.74 & 4.9 & 17.17 & 29.49 & 14.81 & 88.84 \\ AMFMN-soft & 5.05 & 14.53 & 21.57 & 5.05 & 19.74 & 31.04 & 16.02 & 96.98 \\ AMFMN-fusion & 5.39 & 15.08 & 23.4 & 4.9 & 18.28 & 31.44 & 16.42 & 98.49 \\ AMFMN-sim & 5.21 & 14.72 & 21.57 & 4.08 & 17 & 30.6 & 15.53 & 93.18 \\ CABIR & 8.59 & 16.27 & 24.13 & 5.42 & 20.77 & 33.58 & 18.12 & 108.76 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of the results of all models on the dataset RSICD. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline  & & \multicolumn{6}{c}{**UCM Dataset**} \\ \hline \multirow{2}{*}{**Method**} & \multicolumn{3}{c}{**Text Retrieval**} & \multicolumn{6}{c}{**Image Retrieval**} \\  & **R@1** & **R@5** & **R@10** & **R@1** & **R@5** & **R@10** & **mR** & **R@sum** \\ \hline VSE++ & 12.38 & 44.76 & 65.71 & 10.1 & 31.8 & 56.85 & 36.93 & 221.6 \\ SCAN t2i & 14.29 & 45.71 & 67.62 & 12.76 & 50.38 & 77.24 & 44.67 & 268 \\ SCAN i2t & 12.85 & 47.14 & 69.52 & 12.48 & 46.86 & 71.71 & 43.43 & 260.56 \\ MFTN & 10.47 & 47.62 & 64.29 & 14.19 & 52.38 & 78.95 & 44.65 & 267.9 \\ AMFMN-soft & 12.86 & 51.9 & 66.67 & 14.19 & 51.71 & 78.48 & 45.97 & 275.81 \\ AMFMN-fusion & 16.67 & 45.71 & 68.57 & 12.86 & 53.24 & 79.43 & 46.08 & 276.48 \\ AMFMN-sim & 14.76 & 49.52 & 68.1 & 13.43 & 51.81 & 76.48 & 45.68 & 274.1 \\ CABIR & 15.17 & 45.71 & 72.85 & 12.67 & 54.19 & 89.23 & 48.3 & 289.82 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparison of results of all models over the UCM-Captions dataset.