Abstract: A system for training a neural network includes a neural network configured to receive a training input in an image space and produce an enhanced image. The system further includes an error signal generator configured to compare the enhanced image to a ground truth and generate an error signal that is communicated back to the neural network to train the neural network. Additionally, the system includes a neural input enhancer configured to modify the training input in response to receiving at least one of an output from the neural network or the error signal. Modifying the training input improves one of an efficiency or a training result of the neural network beyond the communication of the error signal to only the neural network.

Abstract: The disclosure generally relates to the artificial intelligence (AI) automatic methods, computer program product, and systems and methodology for dietary and medical treatment planning, food waste estimation, analyzing three-dimensional food image construction, measurement, nutrient estimation, nutritional assessment, evaluation, prediction and management. More particularly, the embodiments described herein relate to utilizing an AI-based algorithm that can automatically, detect food items from images acquired by cameras for dietary assessment, dietary planning, and for estimating food waste. In one aspect, the method may include food calorie estimation techniques using machine learning and computer vision techniques for dietary assessment. In another aspect, the tools may apply to personalized nutrition. The method may also include the automation of nutrition planning.

Abstract: A method comprising: obtaining a plurality of data sets, each of the plurality of data sets being generated, at least in part, by using by a different one of a plurality of sensors, each of a plurality of sensors including a wearable sensor that is worn by a user or a sensor that is positioned at a same location as the user; combining the plurality of data sets to produce a fused data set; processing the fused data set to identify at least one of a performance of the user in completing a task, a cognitive load of the user, and/or one or more objects that are positioned at the same location as the user; and outputting an indication of a state of the user based on an outcome of the processing.

Abstract: A method and system for creating hypercomplex representations of data includes, in one exemplary embodiment, at least one set of training data with associated labels or desired response values, transforming the data and labels into hypercomplex values, methods for defining hypercomplex graphs of functions, training algorithms to minimize the cost of an error function over the parameters in the graph, and methods for reading hierarchical data representations from the resulting graph. Another exemplary embodiment learns hierarchical representations from unlabeled data. The method and system, in another exemplary embodiment, may be employed for biometric identity verification by combining multimodal data collected using many sensors, including, data, for example, such as anatomical characteristics, behavioral characteristics, demographic indicators, artificial characteristics.

Abstract: Embodiments of reversible systems and methods for fast, secure and efficient transmission, storage, and protection of digital multimedia are disclosed. The embodiments may have the ability to simultaneously compress and encrypt digital data in order to concurrently reduce data size and prevent reconstruction without the proper encryption key. Embodiments of a method may include pre-processing data to optimize the size of data segments to be compressed, transforming the data for improving the compressibility of the before-mentioned data segments, processing the data sequentially to generate predictive statistical models, encoding the data for simultaneously encrypting and compressing data segments using a keystream, and increasing both the compression ratio and security of these encoding processes using a block cipher. Embodiments of these methods may be suitable for use on both encrypted and unencrypted media.

Abstract: Adaptive methods and apparatuses include compressing, recompressing, decompressing, and transmitting/storing digitized media data, such as text, audio, image, and video. Methods may include partitioning data; transforming partitioned data; analyzing partitioned data; organizing partitioned data, predicting partitioned data; partially or fully encoding partitioned data partially or fully decoding partitioned data, and partially or fully restructuring the original data.

Abstract: A method and system for creating hypercomplex representations of data includes, in one exemplary embodiment, at least one set of training data with associated labels or desired response values, transforming the data and labels into hypercomplex values, methods for defining hypercomplex graphs of functions, training algorithms to minimize the cost of an error function over the parameters in the graph, and methods for reading hierarchical data representations from the resulting graph. Another exemplary embodiment learns hierarchical representations from unlabeled data. The method and system, in another exemplary embodiment, may be employed for biometric identity verification by combining multimodal data collected using many sensors, including, data, for example, such as anatomical characteristics, behavioral characteristics, demographic indicators, artificial characteristics.

Abstract: A method and system for evaluating prostate cancer needle biopsy images for cancer using the nuclei information. The various embodiments of the present invention include the different methods which could be used distinctly or in unification to automatically diagnose, classify, and report the results for the prostate cancer needle biopsy images. Different feature sets are targeted for distinct methods and system, for instance, structural, textural, and geometrical features are utilized for cancer detection, morphological features for Gleason scoring. The invention provides a system to generate the cancer aggressive maps for the whole slide needle biopsy images to help detect the malignancy of prostate cancer. The invention provides the system to perform N-scoring on the prostate cancer tissue samples. The invention also provides the system to generate pathology report automatically.

Abstract: Disclosed are various embodiments of a system or method for the transparent handling of real-time streaming application-level data. The disclosed embodiments permit the identification and modification of specified file patterns from within the live stateful data transactions across computer networks. The system includes a unidirectional in-line communications data stream handler, stream pattern detector, stream file modification processor, and memory management subsystem. Embodiments of the disclosure may include devices permitting incoming network data streams to be captured, processed, and selectively modified when implemented on a digital streaming network communications line. One embodiment of the system includes techniques for mitigation of malicious software directed against software based network connected systems. Other embodiments may make use of approaches for digital data hiding and covert channel obfuscation operations on digital multimedia files being transferred through the system.

Abstract: Systems and methods for detection, grading, scoring and tele-screening of cancerous lesions are described. 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.

Abstract: Systems, apparatuses, and methods provide various progressive, bit-level representations of digital data that are useful for a variety of systems and applications within the fields of machine learning, signal and data processing, and data analytics. Systems, apparatus, and methods for such representations incorporate one or more systems for machine learning, predicting, compressing and decompressing data, and are progressive such that the representations embody a sequential organization of information that prioritizes more information over less significant information. Embodiments of the present disclosure include systems for denoising, enhancing, compressing, decompressing, storing, and transmitting digitized media such as text, audio, image, and video. Methods can include partitioning data, modeling partitioned data, predicting partitioned data, transforming partitioned data, analyzing partitioned data, organizing partitioned data, and partially or fully restructuring the original data.

Abstract: Systems and methods for detection, grading, scoring and tele-screening of cancerous lesions are described. 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.

Abstract: The present invention relates to systems and methods of hierarchical image representation and removal of haze for images, graphics, photographic images, videos, and real-time video. The invented systems/methods may include the configurations and/or steps of: (1) Applying a color space transformation; (2) Computing channels corresponding to the color and content; (3) Decomposing the content channels based on the statistical distribution; (4) Computing image enhancement on decomposed channels; (5) Performing image enhancement algorithms on color channels; (6) Adjusting color parameters; (7) Computing the inverse color transformation to take the image back to the original color space. In embodiments, a method is provided that includes generating a hierarchical representation and segmentation of the image.

Abstract: Disclosed are various embodiments of a system or method for the transparent handling of real-time streaming application-level data. The disclosed embodiments permit the identification and modification of specified file patterns from within the live stateful data transactions across computer networks. The system includes a unidirectional in-line communications data stream handler, stream pattern detector, stream file modification processor, and memory management subsystem. Embodiments of the disclosure may include devices permitting incoming network data streams to be captured, processed, and selectively modified when implemented on a digital streaming network communications line. One embodiment of the system includes techniques for mitigation of malicious software directed against software based network connected systems. Other embodiments may make use of approaches for digital data hiding and covert channel obfuscation operations on digital multimedia files being transferred through the system.

Abstract: Disclosed herein is an automated system comprising methods for improving image quality and image features by using feedback methodologies. More particularly, the systems and methods utilize a feedback loop that takes corrective actions based on the difference between the desired and the actual quality of the image in the enhancement system. The systems and methods include a multi-level design along with feedback loops between the current iteration and each previous iteration so that a measure can control the output by providing inputs to the imaging systems. By evaluating the difference between the computed measure of an enhanced image and its desired image, the system can supply a corrective action. If the system undergoes some image change that affects the regulated image, it can sense this change and force itself back to the desired enhanced image.

Abstract: Adaptive methods and apparatuses include compressing, recompressing, decompressing, and transmitting/storing digitized media data, such as text, audio, image, and video. Methods may include partitioning data; transforming partitioned data; analyzing partitioned data; organizing partitioned data, predicting partitioned data; partially or fully encoding partitioned data partially or fully decoding partitioned data, and partially or fully restructuring the original data.

Abstract: Embodiments of reversible systems and methods for fast, secure and efficient transmission, storage, and protection of digital multimedia are disclosed. The embodiments may have the ability to simultaneously compress and encrypt digital data in order to concurrently reduce data size and prevent reconstruction without the proper encryption key. Embodiments of a method may include pre-processing data to optimize the size of data segments to be compressed, transforming the data for improving the compressibility of the before-mentioned data segments, processing the data sequentially to generate predictive statistical models, encoding the data for simultaneously encrypting and compressing data segments using a keystream, and increasing both the compression ratio and security of these encoding processes using a block cipher. Embodiments of these methods may be suitable for use on both encrypted and unencrypted media.

Abstract: 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.

Abstract: Methods and systems for securing digital imagery are provided. In one respect, embedding, compression, encryption, data hiding, and other imaging processing techniques and systems may be provided for digital image security. In one non-limiting example, a method for producing a compressed and encrypted image is provided. An image may be converted into a binary bit stream, and the bit stream may be decomposed into a plurality of segments. A binary sequence based on a first key may be generated and may be used to generate a code matrix. A distance between the code matrix and the distance may be determined for each of the plurality of segments. Using a combined first and second key, a compressed and encrypted image may be obtained.

Abstract: Methods and systems for securing digital imagery are provided. In one respect, embedding, compression, encryption, data hiding, and other imaging processing techniques and systems may be provided for digital image security. In one non-limiting example, a method for producing a compressed and encrypted image is provided. An image may be converted into a binary bit stream, and the bit stream may be decomposed into a plurality of segments. A binary sequence based on a first key may be generated and may be used to generate a code matrix. A distance between the code matrix and the distance may be determined for each of the plurality of segments. Using a combined first and second key, a compressed and encrypted image may be obtained.