Can inception resnet address mapping the cross channel correlation and spatial correlation?
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Inception ResNet can address both the cross-channel correlation and spatial correlation. The model incorporates a new block called Spatio-Temporal Channel Correlation (STC) that models correlations between channels of a 3D CNN with respect to temporal and spatial features . This block can be added as a residual unit to different parts of the network, improving its performance on datasets such as Kinetics, HMDB51, UCF101, and others . Additionally, the Inception Parallel Attention Network (IPAN) is proposed to perform small object detection in remote sensing images. IPAN contains a multiscale attention module, a contextual attention module, and a channel attention module, which extract rich multiscale, contextual features and interdependencies of global features in different channels . These attention mechanisms contribute to precise results in small object detection, especially in complex scenes and/or in the presence of occlusion .
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| The provided paper does not mention anything about inception resnet or mapping cross channel correlation and spatial correlation. | |
Open access•Posted Content | No, the paper does not mention the use of Inception ResNet for addressing cross channel correlation and spatial correlation. |
| No, the paper does not mention anything about Inception ResNet or its ability to address cross-channel correlation and spatial correlation. |
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