Benchmarking of CNNs for Low-Cost, Low-Power Robotics Applications



Available benchmarks for object classification and detection using Convolutional Neural Networks (CNNs) focus on evaluating accuracy only. This is reflected in the state-of-the-art CNNs as they provide high accuracy at the cost of increasing the number of parameters which translates into a large number of operations. However, constrained environments like low-cost and low-power robots running on batteries commonly used by designers and hobbyists are required to obtain good performance at the minimal power consumption...