Abstract: An edge device performs automated visual inspection on a production line. A sequence of item images is received, and patch-level feature embeddings are extracted for each image. During live operation, a memory bank modeling normal behavior is built by computing distances between patch embeddings and existing entries and appending embeddings whose distance exceeds a dynamic add-threshold derived from a running mean and standard deviation of prior distances. For a candidate image, nearest-neighbor distances from its patches to the memory bank are computed and aggregated into an image-level anomaly score. A prediction threshold is calibrated by synthesizing defects from normal images, scoring both perturbation-augmented and normal images to obtain score distributions, and selecting a threshold that discriminates between them. The candidate image is classified as defective or normal by comparing its anomaly score to the calibrated threshold.

Abstract: Data is received that includes a feed of images of a plurality of objects passing in front of each of a plurality of inspection camera modules forming part of each of a plurality of stations. The stations can together form part of a quality assurance inspection system. The objects when combined or assembled, can form a product. The received data derived from each inspection camera module can be separately analyzed using at least one image analysis inspection tool. The analyzing can include visually detecting a unique identifier for each object. The images are transmitted with results from the inspection camera modules along with the unique identifiers to a cloud-based server to correlate results from the analyzing for each inspection camera module on an product-by-product basis. Access to the correlated results can be provided to a consuming application or process via the cloud-based server.

Abstract: Data is received that is derived from each of a plurality of inspection camera modules forming part of a quality assurance inspection system. The data includes a feed of images of a plurality of objects passing in front of the respective inspection camera module. Thereafter, the received data is separately analyzed by each inspection camera module using at least one image analysis inspection tool. The results of the analyzing can be correlated for each inspection camera module on an object-by-object basis. The correlating can use timestamps for the images and/or detected unique identifiers within the images and can be performed by a cloud-based server and/or a local edge computer. Access to the correlated results can be provided to a consuming application or process.

Abstract: Data is received that is derived from each of a plurality of inspection camera modules forming part of a quality assurance inspection system. The data includes a feed of images of a plurality of objects passing in front of the respective inspection camera module. Thereafter, the received data is separately analyzed by each inspection camera module using at least one image analysis inspection tool. The results of the analyzing can be correlated for each inspection camera module on an object-by-object basis. The correlating can use timestamps for the images and/or detected unique identifiers within the images and can be performed by a cloud-based server and/or a local edge computer. Access to the correlated results can be provided to a consuming application or process.

Abstract: Data is received that includes a feed of images of a plurality of objects passing in front of each of a plurality of inspection camera modules forming part of each of a plurality of stations. The stations can together form part of a quality assurance inspection system. The objects when combined or assembled, can form a product. The received data derived from each inspection camera module can be separately analyzed using at least one image analysis inspection tool. The analyzing can include visually detecting a unique identifier for each object. The images are transmitted with results from the inspection camera modules along with the unique identifiers to a cloud-based server to correlate results from the analyzing for each inspection camera module on an product-by-product basis. Access to the correlated results can be provided to a consuming application or process via the cloud-based server.