1739 results about "Quality assessment" patented technology

A sleep quality assessment approach involves collecting data based on detected physiological or non-physiological patient conditions. At least one of detecting patient conditions and collecting data is performed using an implantable device. Sleep quality may be evaluated using the collected data by an imlantable or patient-external sleep quality processor. One approach to sleep quality evaluation involves computing one or more summary metrics based on occurrences of movement disorders or breathing disorders during sleep.

Methods and apparatus to automatically generate an image quality metric for an image are provided. An example method includes automatically processing a first medical image using a deployed learning network model to generate an image quality metric for the first medical image, the deployed learning network model generated from a digital learning and improvement factory including a training network, wherein the training network is tuned using a set of labeled reference medical images of a plurality of image types, and wherein a label associated with each of the labeled reference medical images indicates a central tendency metric associated with image quality of the image. The example method includes computing the image quality metric associated with the first medical image using the deployed learning network model by leveraging labels and associated central tendency metrics to determine the associated image quality metric for the first medical image.

A driver performance evaluation and apparatus includes means for generating first data stream representing driver actions, a second data stream representing vehicle movements, a filtering function to eliminate short term actions in both data streams, the generation of a raw score which is independent of timing and the adjustment of the raw score based on a comparison of actual driver action timing to an ideal timing sequence to provide a final score which is an indication of driver performance / proficiency.

A system for automating the quality evaluation of a translation. The system may include a computer having a processor and memory device operably connected to one another. A source text in a first language may be stored within the memory device. A target text comprising a translation of the source text into a second language may also be stored within the memory device. Additionally, a plurality of executables may be stored on the memory device and be configured to, when executed by the processor, independently identify a test sample comprising one or more blocks, each comprising a matched set having a source portion selected from the source text and a corresponding target portion selected from the target text.

A system, method and computer program product for recording customer interactions, analyzing recordings and / or providing quality assessment and / or training is set forth. In an exemplary embodiment of the present invention, a system may include a customer interaction recordation application service provider system, which may include, in an exemplary embodiment, an ambulatory capture device adapted to record at least one audio (and / or video) face-to-face interaction between two parties such as, e.g., between an employee and a customer; an aggregation device which may include a cradle adapted to receive said capture device; an application service provider (ASP) server system adapted for user interactive access and analysis of the at least one captured interaction; and a network coupling the aggregation device to the ASP server system adapted to transmit the at least one captured interaction to the ASP server system upon receipt of the capture device in the cradle.

Automated image quality assessment methods, which include locating a region of interest, region assessment, contrast assessment, blur assessment, and contaminant detection, on video data and high-resolution imagery. Where the blur assessment is performed without a reference image by dividing the region into non-overlapping block, measuring the wavenumber frequency of the blocks and calculating the ratio of the low frequency to high frequency areas.

Automatically determining image quality of a machine generated image may generate a local saliency map of the image to obtain a set of unsupervised features. The image is run through a trained convolutional neural network (CNN) to extract a set of supervised features from a fully connected layer of the CNN, the image convolved with a set of learned kernels from the CNN to obtain a complementary set of supervised features. The set of unsupervised features and the complementary set of supervised features are combined, and a first decision on gradability of the image is predicted. A second decision on gradability of the image is predicted based on the set of supervised features. Whether the image is gradable is determined based on a weighted combination of the first decision and the second decision.

Disclosed are new calculations of packet loss bursts, packet re-ordering, and an indication of relative alternate network path delay metrics, based upon differences between received and expected packet sequence numbers, for determining packet network performance.

A kiosk dispenses and receives recorded optical media using an interconnected central server, through an Internet Service Provider. The central server has databases and processing capabilities and is connected to a credit verification system. The databases collect inventory administration information and customer data (e.g., credit card information and email addresses) from the kiosks. The central server initiates credit verification, sends receipts to customers via email and maintains databases for remote inventory control and administration of the kiosk network. A kiosk may identify a recorded disk for automated restocking and perform quality assessment of a recorded disk. The kiosk may provide publishing-on-demand or act as a portal for remotely served advertisements. The kiosk preferably includes a rotatable carousel with a selection of DVDs. A digital camera captures a digital image of a disk barcode and internal software rotates the image to “read” the barcode, to control inventory and access issues.

A first video signal is accessed, and represented in a first color space with a first color gamut, related to a first dynamic range. A second video signal is accessed, and represented in a second color space of a second color gamut, related to a second dynamic range. The first accessed video signal is converted to a video signal represented in the second color space. At least two color-related components of the converted video signal are mapped over the second dynamic range. The mapped video signal and the second accessed video signal are processed. Based on the processing, a difference is measured between the processed first and second video signals. A visual quality characteristic relates to a magnitude of the measured difference between the processed first and second video signals. The visual quality characteristic is assessed based, at least in part, on the measurement of the difference.

An apparatus or method of efficiently coding high resolution video using texture analysis and synthesis techniques in a scalable video coding framework. A high-resolution video signal is spatially downsampled and encoded into a base-layer. Texture and structure information are extracted from the downsampled signal and base-layer for use by a texture synthesizer. The texture synthesizer is structurally and texturally aware utilizing edge information from a base-layer of the synthesizer to improve synthesis. After synthesis, a video quality assessor directs enhancement-layer coding of unacceptably synthesized areas by alternate (non-textural) coding means, such as conventional AVC or MPEG-2 coding. In one mode, the quality assessor iteratively improves synthesis of certain blocks to make them acceptable for enhancement-layer coding. The apparatus or method outputs a bit stream, or bit streams, containing both the coded base-layer and the enhancement-layer.

A face authentication system includes a data input section for obtaining three-dimensional data concerning a face area of a subject at multiple points, and a processor for performing a registration process or a verification process of authentication data of the subject based on the three-dimensional data. The processor has a quality rater for rating a quality of the three-dimensional data with respect to each of the points of the three-dimensional data to generate quality data, and a quality distribution deriving section for deriving a distribution of the quality with respect to the face area, based on the quality data.

A method combining analytic hierarchy process and fuzzy algorithm is provided to evaluate grid electricity quality, including establishing a power quality comprehensive evaluation index system, realizing a comprehensive evaluation of the grid electricity quality status and grid electricity quality in different areas and so on. The invention overcomes the limitation of traditional single-index and single-point power quality evaluation, forming a comprehensive and practical power quality evaluation index system with technical and data support provided for the safe and stable operation of electricity grid.

The invention discloses a pronunciation quality assessment and error detection method based on the fusion of multiple characteristics and multiple systems, which carries out assessment and error detection on pronunciation quality by a method utilizing multiple characteristic parameters to describe pronunciation quality and utilizing multiple inspecting systems to mutually fuse, and comprises the following steps: recognizing voice and automatically segmenting and aligning the voice; extracting the characteristic parameters used for voice quality assessment and error detection; acquiring pronunciation quality assessment and error detection model training data; training a plurality of pronunciation quality assessment and error detection systems; fusing a plurality of pronunciation quality assessment and error detection systems; and assessing pronunciation quality and detecting pronunciation errors. By utilizing the invention, multiple voice characteristics are effectively utilized, and multiple assessment and detection system are fully utilized and perform information fusion, thereby maximally exerting the advantages of various characteristics and systems, and ensuring the accuracy and reliability of pronunciation assessment and error detection.

A method for training a neural network to perform assessments of image quality is provided. The method includes: inputting into the neural network at least one set of images, each set including an image and at least one degraded version of the image; performing comparative ranking of each image in the at least one set of images; and training the neural network with the ranking information. A neural network and image signal processing tuning system are disclosed.

A method and system for image quality assessment is disclosed. The image quality assessment method is a no-reference method for objectively assessing the quality of medical images. This method is guided by the human vision model in order to accurately reflect human perception. A region of interest (ROI) of medical image is divided into non-overlapping blocks of equal size. Each of the blocks is categorized as a smooth block, a texture block, or an edge block. A perceptual sharpness measure, which is weighted by local contrast, is calculated for each of the edge blocks. A perceptual noise level measure, which is weighted by background luminance, is calculated for each of the smooth blocks. A sharpness quality index is determined based on the perceptual sharpness measures of all of the edge blocks, and a noise level quality index is determined based on the perceptual noise level measures of all of the smooth blocks. An overall image quality index can be determined by using task specific machine learning of samples of annotated images. The image quality assessment method can be used in applications, such as video / image compression and storage in healthcare and homeland security, and band-width limited wireless communication.

A system is configured to calculate an evaluation index of sample ink amount data from a color difference evaluation index and an image quality evaluation index and create a profile on the basis of a sample with a high rating value. When the image quality evaluation index is predicted, the image quality evaluation index corresponding to any sample ink amount data is estimated based on a profile produced on the basis on actual evaluation. A printer driver is configured to create a plurality of profiles by using different indices in this system and to perform color conversion by using the plurality of profiles. The plurality of profiles are appropriately selected according to the user's needs, printing conditions, and type of printing object image.

There is described an indicia reading terminal that can be operative to capture a succession of frames of image data and that can be operative so that a certain frame of the succession of frames is subject to quality evaluation processing where a result of the quality evaluation processing is responsive to one or more of an incidence and sharpness of edge representations of the frame of image data.

System for enhancing existing quality monitoring tools for monitoring and guiding agent performance within call centers, each of which provided with a plurality of agent terminals, a plurality of agent audio interfaces, and a plurality of software applications. The proposed system comprises a module for quality evaluation of agents skills and / or of compliance with business processes; a database for storing the results of the evaluation module, in the form of a plurality of profiles of performance; a Call Analysis System (CAS) connected to the database and with the software applications, for retrieving the profile of performance associated with an agent and for generating and transmitting a visual or textual or audio input regarding corrective and / or preventive action(s) required during the current interaction, to an agent terminal, based on the performance profile, and / or on acquired real-time call-based information, as defined by predetermined criteria.

The invention discloses a disease knowledge map construction method and a system, a device and a storage medium thereof, belonging to the technical field of disease knowledge maps. The disease knowledge map construction method comprises the following steps: extracting or learning entity, attributes and relationships among entities from a multi-source database to form ontological knowledge representation; B. knowledge fusion: integrate knowledge to eliminate contradictions and ambiguity; C. Knowledge processing: After quality assessment, the fused knowledge is added to the knowledge base. It also includes disease knowledge mapping platform system, equipment and storage medium. Aiming at the problems existing in the prior art, it extracts entities, attributes and their relationships from multiple data sources, and fuses and processes them, so as to quickly construct a normalized and standardized disease knowledge map.

The invention provides a finger-vein image quality evaluation method and system based on a convolutional neural network. The method includes: labeling the quality of finger-vein gray images, building a training sample set, and using the training sample set to train the convolutional neural network; inputting one optional gray image and a binary image into trained models, selecting the output of second full connection layers in two convolutional neural network models as the depth feature vectors of the input gray image and the binary image; connecting the two depth feature vectors to form a united expression vector, inputting the united expression vector into a support vector machine for training, and using a probability support vector machine to calculate the quality of a predicted finger-vein image. By the evaluation method and system, finger-vein image quality evaluation precision can be increased to a large extent, and the identification performance of a certification system can be improved.