Dynamic Inference Techniques in Convolutional Neural Networks: A Review
The demand for more accurate Convolutional Neural Networks (CNNs) has led to increasingly deep and computationally expensive models. These architectures face limiting deployment and resource constraints when implemented. Static CNN models treat all input samples with identical computational density. These models are in...