Abstract: Methods and systems for interactive image analysis include receiving a selection of a region of an image and a request for analysis of the selection at an interface layer, transferring the selection and the request to an interpretation layer for analysis, dividing the selected region of the image into a plurality of sub-sections optimized for parallel computation to provide an analysis result that minimizes perceptible delay between receiving the request and receipt of results, analyzing the sub-sections using one or more execution nodes using a copy of the image stored in a shared memory, and providing combined analysis results to the interface layer for display.

Abstract: A method and systems for cloud-based digital pathology include scanning received slides that include a pathology sample to produce a sample image in a shared memory, analyzing the sample image using one or more execution nodes, each including one or more processors, according to one or more analysis types to produce intermediate results, transmitting some or all of the sample image to a client device, further analyzing the sample image responsive to a request from the client device to produce a final analysis based on the intermediate results, and transmitting the final analysis to the client device.

Abstract: Methods and systems for digital pathology with low-latency analytics include determining potential regions of interest within an image in accordance with one or more high-priority analyses, dividing the potential regions of interest into a plurality of sub-sections optimized for parallel computation, analyzing the sub-sections using one or more execution nodes, each including one or more processors, using a copy of the image stored in a shared memory according to the one or more high-priority analyses, and storing an intermediate analysis result based on analysis results from the one or more execution nodes in a shared memory.

Abstract: Methods and systems for digital pathology with low-latency analytics include determining potential regions of interest within an image in accordance with one or more high-priority analyses, dividing the potential regions of interest into a plurality of sub-sections optimized for parallel computation, analyzing the sub-sections using one or more execution nodes, each including one or more processors, using a copy of the image stored in a shared memory according to the one or more high-priority analyses, and storing an intermediate analysis result based on analysis results from the one or more execution nodes in a shared memory.

Abstract: A method and systems for cloud-based digital pathology include scanning received slides that include a pathology sample to produce a sample image in a shared memory, analyzing the sample image using one or more execution nodes, each including one or more processors, according to one or more analysis types to produce intermediate results, transmitting some or all of the sample image to a client device, further analyzing the sample image responsive to a request from the client device to produce a final analysis based on the intermediate results, and transmitting the final analysis to the client device.

Abstract: Methods and systems for interactive image analysis include receiving a selection of a region of an image and a request for analysis of the selection at an interface layer, transferring the selection and the request to an interpretation layer for analysis, dividing the selected region of the image into a plurality of sub-sections optimized for parallel computation to provide an analysis result that minimizes perceptible delay between receiving the request and receipt of results, analyzing the sub-sections using one or more execution nodes using a copy of the image stored in a shared memory, and providing combined analysis results to the interface layer for display.

Abstract: The present invention provides a method and apparatus for compressing images of financial instruments and other documents. The method of the present invention includes the steps of scanning a plurality of documents to obtain an electronic image of each document; identifying a static portion in the electronic image of each of the documents, containing information which remains substantially unchanged for the plurality of documents, by locating and reading a document identifier in the image; storing the document identifier in a database; identifying a dynamic portion, typically containing distinct information for each of the documents, in each of the electronic images; isolating the dynamic portion from the static portion within the image to obtain a dynamic image containing only the dynamic portion; and storing the dynamic image in the database. The present invention provides efficient techniques for identifying and isolating dynamic information in a document, such as handwritten text on a check.

Abstract: A measure of the correlation or degree of closeness between an input data pattern and a stored data pattern is achieved directly from content-addressable memory cells which are realized in accordance with the principles of the present invention to provide a match/non-match output indication which is summable with other such match/non-match output indications on a match bus line for computing the correlation or degree of closeness measure. Each content-addressable memory cell includes a single bit, static random access memory cell and a comparing logic gate connected jointly to the output of the static random access memory cell and the bit bus line for the single bit of the input data pattern. Output of the comparing logic gate is connected to the match bus line and is generated as a fixed amount of current which can be summed with other current on the match bus line. The output stage of the comparing gate is thus operated as a current source.

Abstract: A method for improved thinning or skeletonizing handwritten characters or other variable-line-width images. The method scans a template set over the image to be thinned. Each template has a specific arrangement of dark and light pixels. At least one of those templates includes either more than three pixels per row or more than three rows of pixels. An odd number is good choice. Moreover, the templates are chosen so that each template can unconditionally delete image pixels without consideration of the effect of such deletions on the behavior of the other templates. Thus the templates are independent of each other.

Abstract: Realization of a reconfigurable neuron for use in a neural network has been achieved using analog techniques. In the reconfigurable neuron, digital input data are multiplied by programmable digital weights in a novel connection structure whose output permits straightforward summation of the products thereby forming a sum signal. The sum signal is multiplied by a programmable scalar, in general, 1, when the input data and the digital weights are binary. When the digital input data and the digital weights are multilevel, the scalar in each reconfigurable neuron is programmed to be a fraction which corresponds to the bit position in the digital data representation, that is, a programmable scalar of 1/2, 1/4, 1/8, and so on. The signal formed by scalar multiplication is passed through a programmable build out circuit which permits neural network reconfiguration by interconnection of one neuron to one or more other neurons.

Abstract: A new associative computation network that is capable of storing multi-bit vectors includes a decision network and a feedback arrangement that, functionally, is separable into serially connected networks. The first network has its inputs connectd to the outputs of the decision network and is arranged to develop sets of excitatory and inhibitory drive signals. Each set corresponds to a stored vecor. For each different output state of the decision network, a different one of the drive signal sets appears at the output of the first network. The output leads of the first network, which may also be employed as the input interface leads, are connected to the second network. The second network develops output signals, applied to inputs of the decision network, which are proportional to the projection of the input signals applied to the second network on the stored vectors.

Abstract: The operation of neural networks begins with the initialization of the system with the information to be processed. Presently, this initialization is performed by pinning the system with rather large analog or digital signals representing this information. The problems associated with the high power required for such initialization are eliminated and accuracy is maintained by utilizing a specific set of input points and appropriately positioned switches. In particular, a switch corresponding to each amplifier is introduced, and the initializing data is introduced between the amplifier and this switch.