Abstract: The invention is a computer implemented process directed towards a Deep learning neural network architecture to create object detection model using high resolution images. More specifically, the invention is directed towards enhancing the classification accuracy and reliability of edge inspection in contact lenses. The invention is a Computer implemented process to represent a software architecture comprising software components and their inter dependencies that represents the core functional modules of an application.

Abstract: The present disclosure generally relates to upgrading existing automated legacy systems. More specifically, the present disclosure relates to system and method for a proxy interpreter system to collect and consolidate the setup, configuration, operation and quality inspection data from a plurality of interfacing devices and controllers of legacy systems and subsequently build a Reinforcement learning module using the consolidated data to perform all the functions automatically without the intervention of a human operator. The consolidated data in the proxy interpreter module may be further analysed using Deep learning methods for data analytics and artificial intelligence to reliably and consistently classify the defect criteria of products to further enhance the quality of the inspection. The defect criteria classification enables the Proxy interpreter system to highlight potential problems and aid in preventive maintenance of the legacy automated systems.

Abstract: A system for detecting refractive power of a dry ophthalmic lens under inspection, comprising: a) a top camera 10 arranged to view the ophthalmic lens 40 through an optical module 25; b) an optically transparent surface 30 to position the ophthalmic lens 40 for inspection; c) a precisely calibrated glass target 50 suitably positioned on a transparent plate 60, arranged to achieve an image of the ophthalmic lens 40 overlaid with the image of the pattern on the target 50; d) at least one light source having multiple wavelength LEDs to capture different images under multiple lighting conditions.

Abstract: The invention is a computer implemented process directed towards a Deep learning neural network architecture to create object detection model using high resolution images. More specifically, the invention is directed towards enhancing the classification accuracy and reliability of edge inspection in contact lenses. The invention is a Computer implemented process to represent a software architecture comprising software components and their inter dependencies that represents the core functional modules of an application.