Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assess image quality using adaptive non-overlapping mean estimation are disclosed. Example apparatus disclosed herein include a machine learning system to be trained to classify image quality. Disclosed example apparatus also include a feature extractor to apply a blur filter to a first image to determine a blurred image, determine a blur feature value for the first image, the blur feature value to represent an amount the first image differs from the blurred image, and apply a vector of feature values associated with the first image to the machine learning system, the vector of feature values including the blur feature value. Disclosed example apparatus further include an image classifier to classify image quality associated with the first image based on an output of the machine learning system responsive to the vector of feature values associated with the first image.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assess image quality using adaptive non-overlapping mean estimation are disclosed. Example apparatus disclosed herein include a machine learning system to be trained to classify image quality. Disclosed example apparatus also include a feature extractor to apply a blur filter to a first image to determine a blurred image, determine a blur feature value for the first image, the blur feature value to represent an amount the first image differs from the blurred image, and apply a vector of feature values associated with the first image to the machine learning system, the vector of feature values including the blur feature value. Disclosed example apparatus further include an image classifier to classify image quality associated with the first image based on an output of the machine learning system responsive to the vector of feature values associated with the first image.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assess image quality using adaptive non-overlapping mean estimation are disclosed. Example image quality assessment methods disclosed herein include replacing respective blocks of pixels of a first image with mean values of the respective blocks of pixels to determine a second image having a smaller size than the first image. Disclosed example image quality assessment methods also include determining a vector of features for the second image. Disclosed example image quality assessment methods further include applying the vector of features to a neural network, and classifying a quality of the first image based on an output of the neural network.

Abstract: Methods, apparatus, systems and articles of manufacture (e.g., physical storage media) to assess image quality using adaptive non-overlapping mean estimation are disclosed. Example image quality assessment methods disclosed herein include replacing respective blocks of pixels of a first image with mean values of the respective blocks of pixels to determine a second image having a smaller size than the first image. Disclosed example image quality assessment methods also include determining a vector of features for the second image. Disclosed example image quality assessment methods further include applying the vector of features to a neural network, and classifying a quality of the first image based on an output of the neural network.

Abstract: A process to reduce or prevent biofouling, by destroying or deactivating microbiological content of feedwater, or other liquid, prior to its entrance into membranes or process equipment, such as heat transfer equipment. The process comprises the use of electrical discharge and/or electric fields to destroy microbes that result in the biofouling of surfaces. By destroying the microbiological content of the water the microbiology no longer is able to create a restricting biofilm upon or within said process equipment.

Abstract: A process to reduce or prevent biofouling, by destroying or deactivating microbiological content of feedwater, or other liquid, prior to its entrance into membranes or process equipment, such as heat transfer equipment. The process comprises the use of electrical discharge and/or electric fields to destroy microbes that result in the biofouling of surfaces. By destroying the microbiological content of the water the microbiology no longer is able to create a restricting biofilm upon or within said process equipment.