THE MASSIVE AMOUNT OF DATA PRESENT IN AN IMAGE PRESENTS PROBLEMS WHEN PROCESSING THE IMAGE USING A NEURAL NETWORK. SIGNIFICANT REDUCTIONS IN THE SIZE OF THE NETWORK CAN BE ACCOMPLISHED IF THE IMAGE IS PREPROCESSED USING AN OPTICAL FEATURE EXTRACTOR OR A DIGITAL SIMULATION OF AN OPTICAL PROCESSOR. THE PAPER DETAILS THE MODEL AND ALGORITHM USED TO REDUCE THE SIZE OF THE PROPOSED NETWORK AND TO ELIMINATE THE EFFECTS OF ANGULAR AMBIGUITY PRESENT IN THE IMAGE.
Microbiology of the food chain - Horizontal method for the detection and enumeration of Clostridium spp. - Part 3: Detection of Clostridium perfringens
Flexible sheets for waterproofing - Plastic and rubber sheets for waterproofing of concrete bridge decks and other trafficked areas of concrete - Definitions and characteristics
Seamless Steel Tubes for Pressure Purposes - Technical Delivery Conditions - Part 4: Non-alloy and alloy steel tubes with specified low temperature properties
