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1784 results about "Feature set" patented technology

Feature set. A group of functions (capabilities, capacities, etc.). When a vendor says "the feature set for the next version of our software is frozen," it means all enhancements and new capabilities have been determined and planned for development.

Systems and methods for automated screening and prognosis of cancer from whole-slide biopsy images

InactiveUS20140233826A1Accurate and unambiguous measureReduce dependenceImage enhancementMedical data miningFeature setProstate cancer
The invention provides systems and methods for detection, grading, scoring and tele-screening of cancerous lesions. A complete scheme for automated quantitative analysis and assessment of human and animal tissue images of several types of cancers is presented. Various aspects of the invention are directed to the detection, grading, prediction and staging of prostate cancer on serial sections/slides of prostate core images, or biopsy images. Accordingly, the invention includes a variety of sub-systems, which could be used separately or in conjunction to automatically grade cancerous regions. Each system utilizes a different approach with a different feature set. For instance, in the quantitative analysis, textural-based and morphology-based features may be extracted at image- and (or) object-levels from regions of interest. Additionally, the invention provides sub-systems and methods for accurate detection and mapping of disease in whole slide digitized images by extracting new features through integration of one or more of the above-mentioned classification systems. The invention also addresses the modeling, qualitative analysis and assessment of 3-D histopathology images which assist pathologists in visualization, evaluation and diagnosis of diseased tissue. Moreover, the invention includes systems and methods for the development of a tele-screening system in which the proposed computer-aided diagnosis (CAD) systems. In some embodiments, novel methods for image analysis (including edge detection, color mapping characterization and others) are provided for use prior to feature extraction in the proposed CAD systems.

Adaptive method and apparatus for forecasting and controlling neurological disturbances under a multi-level control

InactiveUS7146218B2Avoid injuryPrevent and avoid seizureElectroencephalographyElectrotherapyFeature setPupil
A method and apparatus for forecasting and controlling neurological abnormalities in humans such as seizures or other brain disturbances. The system is based on a multi-level control strategy. Using as inputs one or more types of physiological measures such as brain electrical, chemical or magnetic activity, heart rate, pupil dilation, eye movement, temperature, chemical concentration of certain substances, a feature set is selected off-line from a pre-programmed feature library contained in a high level controller within a supervisory control architecture. This high level controller stores the feature library within a notebook or external PC. The supervisory control also contains a knowledge base that is continuously updated at discrete steps with the feedback information coming from an implantable device where the selected feature set (feature vector) is implemented. This high level controller also establishes the initial system settings (off-line) and subsequent settings (on-line) or tunings through an outer control loop by an intelligent procedure that incorporates knowledge as it arises. The subsequent adaptive settings for the system are determined in conjunction with a low-level controller that resides within the implantable device. The device has the capabilities of forecasting brain disturbances, controlling the disturbances, or both. Forecasting is achieved by indicating the probability of an oncoming seizure within one or more time frames, which is accomplished through an inner-loop control law and a feedback necessary to prevent or control the neurological event by either electrical, chemical, cognitive, sensory, and/or magnetic stimulation.

A multi-target tracking method and system based on depth features

The embodiment of the invention provides a multi-target tracking method and system based on depth features. The method comprises the following steps: obtaining detection frame positions correspondingto targets detected in a current frame image and the depth features of the targets; based on the position of the detection frame corresponding to each target in the previous frame of image, obtainingthe prediction position of each target in the current frame by using a Kalman filter; according to the detection frame position corresponding to each target, the prediction position of each target inthe current frame, the depth feature of each target and the depth feature set of each tracker, performing cascade matching on the detection frame corresponding to each target and the tracker by usinga Hungarian algorithm; And calculating an IOU distance matrix between the detection frame on the non-cascade matching and the tracker to be matched, and performing IOU matching between the detection frame and the tracker by using a Hungarian algorithm based on the IOU distance matrix to obtain a final matching set. According to the embodiment of the invention, the target tracking effect under theshielding condition can be effectively improved, and the number of times of ID switching is reduced.

System and method for capturing and detecting symbology features and parameters

This invention provides a system and method for capturing, detecting and extracting features of an ID, such as a 1D barcode, that employs an efficient processing system based upon a CPU-controlled vision system on a chip (VSoC) architecture, which illustratively provides a linear array processor (LAP) constructed with a single instruction multiple data (SIMD) architecture in which each pixel of the rows of the pixel array are directed to individual processors in a similarly wide array. The pixel data are processed in a front end (FE) process that performs rough finding and tracking of regions of interest (ROIs) that potentially contain ID-like features. The ROI-finding process occurs in two parts so as to optimize the efficiency of the LAP in neighborhood operations—a row-processing step that occurs during image pixel readout from the pixel array and an image-processing step that occurs typically after readout occurs. The relative motion of the ID-containing ROI with respect to the pixel array is tracked and predicted. An optional back end (BE) process employs the predicted ROI to perform feature-extraction after image capture. The feature extraction derives candidate ID features that are verified by a verification step that confirms the ID, creates a refined ROI, angle of orientation and feature set. These are transmitted to a decoding processor or other device.

Optical method and system for rapid identification of multiple refractive index materials using multiscale texture and color invariants

ActiveUS20050126505A1Rapid and accurate identificationRapid and accurate and classificationClimate change adaptationCharacter and pattern recognitionGabor wavelet transformFeature set
An innovative optical system and method is disclosed for analyzing and uniquely identifying high-order refractive indices samples in a diverse population of nearly identical samples. The system and method are particularly suitable for ultra-fine materials having similar color, shape and features which are difficult to identify through conventional chemical, physical, electrical or optical methods due to a lack of distinguishing features. The invention discloses a uniquely configured optical system which employs polarized sample light passing through a full wave compensation plate, a linear polarizer analyzer and a quarter wave retardation plate for producing vivid color bi-refringence pattern images which uniquely identify high-order refractive indices samples in a diverse population of nearly visually identical samples. The resultant patterns display very subtle differences between species which are frequently indiscernable by conventional microscopy methods. When these images are analyzed with a trainable with a statistical learning model, such as a soft-margin support vector machine with a Gaussian RBF kernel, good discrimination is obtained on a feature set extracted from Gabor wavelet transforms and color distribution angles of each image. By constraining the Gabor center frequencies to be low, the resulting system can attain classification accuracy in excess of 90% for vertically oriented images, and in excess of 80% for randomly oriented images.

Method and system for identifying crop diseases and pests based on Android mobile phone platform

The invention relates to a method for identifying crop diseases and pests based on an Android mobile phone platform. The method comprises the steps that disease and pest pictures are taken through a camera and stored in an SD card of an Android mobile phone; the disease and pest pictures are preprocessed; features of the preprocessed disease and pest pictures are extracted; feature training is carried out on a feature set, and sample set data are trained through an SVM method to obtain a disease and pest diagnosis model; SVM classification is carried out through the disease and pest diagnosis model, a classification and diagnosis result of the diseases and pests is obtained, and prevention and treatment methods are fed back to a mobile phone user. The invention further discloses a system for identifying crop diseases and pests based on the Android mobile phone platform. Through picture preprocessing and feature extraction carried out on the disease and pest pictures, the disease and pest pictures are classified through the SVM learning method to set up the disease and pest diagnosis model, the purpose of identifying the disease and pest pictures is achieved, and the user only needs to take pictures for the diseases and pests in an aligned mode through the mobile phone, and identification efficiency is high.
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