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This document presents a novel crowd density estimation method using a multichannel dense grouping network (McDGM) to address challenges such as uneven crowd distribution and illumination changes. The proposed approach incorporates an improved grouping convolution block to enhance feature extraction and a new loss function to improve counting accuracy. Experimental results demonstrate that this method outperforms existing techniques on benchmark datasets, indicating its effectiveness in real-world applicati

Author

drshitanshuarya

Language

EN