IJACIS
Open Access
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Vehicle Detection Through Cnn
In this work, a reliable and effective model for the identification of cars in traffic surveillance. Vehicle detection is achieved through the Operation of Convolutional Neural Networks (CNNs), combining high-level and low-level information using feature fusion techniques. The use of static pictures is highly applicable for various operations in traffic surveillance. This makes it possible to identify different-sized cars using different attributes. We get 99.4% training accuracy & 99.3% in testing accuracy.