Lecture by Dr. Ratnesh Kumar "Vehicle Re-identification for Smart Cities: A New Baseline Using Triplet Embedding"

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#vehicle reidentification #artificial intelligence #neural networks

With the proliferation of surveillance cameras enabling smart and safer cities, there is an ever-increasing need to re-identify vehicles across cameras. Typical challenges arising in smart city scenarios include variations of viewpoints, illumination and self occlusions. In this talk we will discuss an exhaustive evaluation of deep embedding losses applied to vehicle re-identification, and demonstrate that using the best practices for learning-embeddings outperform most of the previous approaches in vehicle re-identification.

Vehicle re-identification for smart cities: a new baseline using triplet embedding

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