Abstract: Disclosed are systems, apparatuses, processes, and computer-readable media to detect objects in dynamic lighting conditions. A method of processing image data includes obtaining, at a computing device, a first image of an object at a first position in an environment, obtaining, at the computing device, a second image of the object at a second position in the environment, and determining, at the computing device, movement of the object in the first image and the second image at least in part using an optical flow engine, wherein the optical flow engine is trained based on augmented training data generated using at least one of noise associated with low ambient lighting conditions, noise associated with motion blur due to exposure of an image sensor in low ambient lighting conditions, or brightness variations. The object and/or the computing device may move between the first image and the second image.

Abstract: A model construction method and an apparatus, and a medium and an electronic device are disclosed. The method is applied to a first participant platform, and includes: associating first configuration information pre-created by a first participant with second configuration information pre-created by a second participant; verifying the first configuration information; sending, to a second participant platform corresponding to the second participant, a second creation request for requesting the creation of the federated learning model, to cause the second participant platform to verify the second configuration information creating a first model task on the basis of a first parameter corresponding to the first configuration information; and performing co-training on the basis of the first model task and a second model task, to obtain the federated learning model.