Główne pojęcia
Moment Channel Attention (MCA) framework enhances model capacity by incorporating high-order moments and cross-channel features efficiently.
Statystyki
"Experimental results on classical image classification, object detection, and instance segmentation tasks demonstrate that our proposed method achieves state-of-the-art results, outperforming existing channel attention methods."
Cytaty
"Our findings highlight the critical role of high-order moments in enhancing model capacity."
"MCA block is designed to be lightweight and easily integrated into a variety of neural network architectures."