Balancing Privacy and Performance: This Paper Introduces a Dual-Stage Deep Learning Framework for Privacy-Preserving Re-Identification

Person Re-identification (Person Re-ID) in Machine Learning uses deep learning models like convolutional neural networks to recognize and track individuals across different camera views, holding promise for surveillance and public safety but raising significant privacy concerns. The technology’s capacity to track people across locations increases surveillance and security risks, along with potential privacy issues like […]

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