1. A method for object detection using a neural network, the method comprising: in a training mode: passing a dataset into the neural network; and training the neural network to accurately output a box size and a center location of a first object of interest, wherein the box size corresponds to the smallest possible bounding box around the first object of interest and the center location corresponds to the location of the center of the bounding box; and in an inference mode: passing an image into the neural network, wherein the image is not part of the dataset; automatically identifying a second object of interest; and automatically drawing a box around the second identified object of interest, wherein the box drawn around the second identified object of interest corresponds to the smallest possible bounding box around the second object of interest; wherein the neural network comprises a convolution-nonlinearity step and a recurrent step.