Abstract: In general, the disclosure describes techniques for implementing an MI-based attack detector. In an example, a method includes training a neural network using training data, applying stochastic quantization to one or more layers of the neural network, generating, using the trained neural network, an ensemble of neural networks having a plurality of quantized members, wherein at least one of weights or activations of each of the plurality of quantized members have different bit precision, and combining predictions of the plurality of quantized members of the ensemble to detect one or more adversarial attacks and/or determine performance of the ensemble of neural networks.

Abstract: A method, apparatus and system for enhanced welding visualization include splitting incoming light from the welding environment into at least a first optical path and a second optical path having different light levels using at least one beam splitter. Images of the split light having different light levels are captured using a respective imaging sensor. The images from the respective imaging sensors are fused to create a left-eye fused image and a right-eye fused image. The left-eye fused image is displayed on a display at a location of a left eye of a user and the right-eye fused image is displayed on a display at a location of a right eye of the user to provide a parallax-free, high dynamic range, representation of the welding environment.

Abstract: A method, apparatus and system for enhanced welding visualization include splitting incoming light from the welding environment into at least a first optical path and a second optical path having different light levels using at least one beam splitter. Images of the split light having different light levels are captured using a respective imaging sensor. The images from the respective imaging sensors are fused to create a left-eye fused image and a right-eye fused image. The left-eye fused image is displayed on a display at a location of a left eye of a user and the right-eye fused image is displayed on a display at a location of a right eye of the user to provide a parallax-free, high dynamic range, representation of the welding environment.

Abstract: A video processor that uses a low latency pyramid processing technique for fusing images from multiple sensors. The imagery from multiple sensors is enhanced, warped into alignment, and then fused with one another in a manner that provides the fusing to occur within a single frame of video, i.e., sub-frame processing. Such sub-frame processing results in a sub-frame delay between a moment of capturing the images to the display of the fused imagery.