Abstract: A system for evaluating a workspace surface having one or more objects placed thereon is disclosed. The system may include sensors configured to capture data corresponding to the workspace surface and a controller communicatively coupled to the sensors. The controller may generate an illuminance map of the workspace surface based on the captured data. The controller may generate a clutter entropy level based on the illuminance map and an entropy assessor. The controller may determine whether the clutter entropy level exceeds a clutter threshold. The controller may provide a clutter indication to a user device if the clutter entropy level exceeds the clutter threshold. The controller may identify the objects placed on the workspace surface. The controller may generate a decluttered layout based on the one or more objects and a layout generator.

Abstract: A method for optimizing a neural network is provided, including: (1) capturing, via a first sensor group having a first field of view, a first sample set having a first sensor domain corresponding to the first field of view; (2) capturing, via a second sensor group having a second field of view, a second sample set having a second sensor domain corresponding to the second field of view; (3) generating regions of interest of the second sample set; (4) translating the regions of interest to the first sensor domain; (5) identifying nodes of the neural network which correspond to the translated regions; and (6) optimizing the neural network by at least one of (a) increasing the weight value of the nodes corresponding to the one or more translated regions and (b) decreasing the weight value of the nodes not corresponding to the one or more translated regions.

Abstract: A system for generating two-dimensional images is provided. The system may include a controller configured to receive a three-dimensional design image. The controller may be further configured to generate a fake 2D image based on the 3D design image and one or more 3D image parameters, such as object orientation. The controller may be further configured to generate a realistic 2D image based on the fake 2D image and one or more image features. The controller may be further configured to evaluate a realism value of the realistic 2D image based on one or more real 2D images. The controller may be further configured to evaluate a detected orientation of the realistic 2D image. The controller may be further configured to update the realistic image generator based on the realism value or the detected orientation.