A flow meter includes a background pattern disposed behind a drip chamber, an image sensor, and a processor. The image sensor has a field of view and is configured to view the drip chamber within the field of view. The processor is coupled to the image sensor to receive image data therefrom and captures, using the image sensor, an image of the drip chamber and at least a portion of the background pattern, examines the image, and adjusts a flow rate of fluid flowing through a fluid line in accordance with the examination of the image.

A flow meter includes an image sensor, a coupler, a support member and one or more processors. The coupler is adapted to couple to a drip chamber. The support member is operatively coupled to the coupler. The image sensor has a field of view and is operatively coupled to the support member. The image sensor is positioned to view the drip chamber within the field of view. The processor receives data from the image sensor and is configured to: receive a first image from the image sensor, compare the first image to a second image, and generate a difference image based upon the comparison between the first and second images.

A flow meter includes an image sensor, a coupler, a support member and one or more processors. The coupler is adapted to couple to a drip chamber. The support member is operatively coupled to the coupler. The image sensor has a field of view and is operatively coupled to the support member. The image sensor is positioned to view the drip chamber within the field of view. The processor receives data from the image sensor and is configured to: receive a first image from the image sensor, compare the first image to a second image, and generate a difference image based upon the comparison between the first and second images.

An image processing apparatus counts at least one of the number of pixels having an identical color to a target pixel, the number of pixels having a similar color to the target pixel, and the number of pixels having a different color from the target pixel in a target window, and determines an attribute of the target pixel based on a result of the counting.

A flow meter includes an image sensor, a coupler, a support member and one or more processors. The coupler is adapted to couple to a drip chamber. The support member is operatively coupled to the coupler. The image sensor has a field of view and is operatively coupled to the support member. The image sensor is positioned to view the drip chamber within the field of view. The processor receives data from the image sensor and is configured to: receive a first image from the image sensor, compare the first image to a second image, and generate a difference image based upon the comparison between the first and second images.

An apparatus, system and method for regulating fluid flow are disclosed. The apparatus includes a flow rate sensor and a valve. The flow rate sensor uses images to estimate flow through a drip chamber and then controls the valve based on the estimated flow rate. The valve comprises a rigid housing disposed around the tube in which fluid flow is being controlled. Increasing the pressure in the housing controls the size of the lumen within the tube by deforming the tube, therefore controlling flow through the tube.

A date identification apparatus includes: an isolator that isolates, out of image data generated through capturing of an image of a medium to which a date is assigned using seven-segment characters, date area data to which the date is estimated to be assigned; a binarization converter that binarizes the date area data using a threshold based on luminance and hue; a labeler that subjects the binarized date area data to labeling to extract target area data that is identifiable as a numeral; a numeral identifier that performs a histogram on at least the target area data using a plurality of lines and identifies a numeral on a basis of a peak count in each of the lines; and a date data assigner that assigns date data based on the identified numeral to the image data.

The present disclosure relates to computer-implemented methods, software, and systems for extracting information from documents based on training techniques to generate a document foundation model that is used to initialize a document information extraction model that is fine-tuned to business document specifics. A document information extraction model is initialized based on weights provided from a first pretrained model. Fine-tuning of the document information extraction model is performed based on labeled business documents as second training data. The labeled business documents are labeled and evaluated according to a virtual adversarial training (VAT). Based on the performed fine-tuning, a classifier for classification of information extraction is generated.

The present disclosure discloses a method and system for visual inspection of a target product. The method includes a) receiving an image associated with the target product; generating a plurality of region of interests (ROIs) associated with the image; identifying, based on the plurality of non-terminal ROIs, a first set of features and a second set of features associated with the image. The first set of features and the second set of features are indicative of one of a presence of defect within the image or an absence of defect within the image. The method also includes determining, based on the first set of features and the second set of features, a result of the visual inspection of the target product associated with the image. The result is a success result or a failure result.

In an exemplary embodiment, the invention comprises a principled edit-distance system that performs a method for determining the probability of character errors. In another exemplary embodiment, the invention comprises a post-OCR error correction system that performs a context-sensitive correction method. In another exemplary embodiment, the invention comprises a post-OCR error correction system that performs a comprehensive, unified correction process based on generalized edit distance analysis, wherein the objective is to find a corrected sentence that has the overall smallest edit distance across all levels. In another exemplary embodiment, the invention comprises a post-OCR error correction system that comprises one or more subjective fractional rank-based dictionaries. In another embodiment, the invention comprises a post-OCR error correction system that performs the automatic assignment of rank to words per-document dictionaries.