Embodiments of this application disclose methods, systems, and devices for image region localization and medical image processing. In one aspect, a method comprises acquiring three-dimensional images of a target body part of a patient. The three-dimensional images comprise a plurality of magnetic resonant imaging (MRI) modalities. The method comprises registering a first image set of a first modality with a second image set of a second modality. After the registering, image features of the three-dimensional images are extracted. The image features are fused to obtain fused features. The method also comprises determining voxel types corresponding to voxels in the three-dimensional images according to the fused features. The method also comprises selecting, from the three-dimensional images, target voxels having a preset voxel type, obtaining position information of the target voxels, and localizing a target region within the target body part based on the position information of the target voxels.

There is provided a method for estimating play out resolution of a video delivered to a client device by an encrypted video stream communicated over a network. The method selects a current chunk of the encrypted video stream comprising data packets expected to carry video data of the same level of playout resolution and determines values for a predetermined set of features indicative of conditions in the network. By accessing a pregenerated model, a corresponding set of state transition probabilities is obtained, defining a Markov chain whose states comprise the different levels of resolution. The determined state transition probabilities are then used to calculate, from a first probability distribution arising from a first or previous step in the Markov chain, a second probability distribution for the plurality of states of the Markov chain expected to result from the indicated network conditions.

A method of classifying an interaction captured in a sequence of video. A plurality of people in the video sequence is identified. An action of a first one of the people at a first time is determined. An action of a second one of the people at a second time is determined, the action of the second person being after the action of the first person. A role for the second person at the second time is determined, the role being independent of the determined actions of the first and second person. An interaction between the first person and the second person is classified based on the determined role of the second person and the determined actions of the first and second person.

A system includes a processor configured to provide an immersive virtual environment wherein first and second users can view and edit interaction data corresponding to interactive motion capture for first and second performers who interact with one another in a performance corresponding to the interaction between first and second characters, so as to edit the interaction between the first and second characters and thereby provide edited data corresponding to the performance.

Systems and methods are disclosed to objectively identify sub-second behavioral modules in the three-dimensional (3D) video data that represents the motion of a subject. Defining behavioral modules based upon structure in the 3D video data itselfrather than using a priori definitions for what should constitute a measurable unit of actionidentifies a previously-unexplored sub-second regularity that defines a timescale upon which behavior is organized, yields important information about the components and structure of behavior, offers insight into the nature of behavioral change in the subject, and enables objective discovery of subtle alterations in patterned action. The systems and methods of the invention can be applied to drug or gene therapy classification, drug or gene therapy screening, disease study including early detection of the onset of a disease, toxicology research, side-effect study, learning and memory process study, anxiety study, and analysis in consumer behavior.

Computer vision systems and methods for end-to end training of neural networks are provided. The system generates a fixed point algorithm for dual-decomposition of a maximum-a-posteriori inference problem and trains the convolutional neural network and a conditional random field with the fixed point algorithm and a plurality of images of a dataset to learn to perform semantic image segmentation. The system can segment an attribute of an image of the dataset by the trained neural network and the conditional random field.

Some embodiments of the present disclosure relate to systems and methods including generating, by infrared spectroscopy, spectra data identifying quantities and associated wavelengths of radiation absorption for each of a plurality of wine samples as determined by the infrared spectroscopy; converting the spectra data for each wine sample to a set of discretized data; transforming the discretized data into a visual image representation of each respective wine sample, the visual image representation of each wine sample being an optically recognizable representation of the corresponding converted set of discretized data; and storing a record including the visual image representation of each wine sample in a memory.

An electronic device includes memory circuitry, and processor circuitry having an action detection circuitry configured to operate according to an action detection model for detecting an action based on a machine-learning scheme. The processor circuitry being configured to obtain sensor data; generate, based on the sensor data, a set of features associated with a frame; determine, based on the set, using the action detection model, whether the frame corresponds to a sub-action; apply a nondeterministic finite automaton, NFA, scheme, to the determined sub-action for the frame, wherein the NFA scheme has a set of states associated with corresponding sub-actions and is configured to output one or more action classes; determine, using the NFA scheme, an action class; detect the action based on the action class; and increment an action counter based on the detected action.

A system, method and apparatus for executing a bioinformatics analysis on genetic sequence data includes a quantum computing device formed of a set of hardwired quantum logic circuits interconnected by a plurality of superconducting connections to process information represented as a quantum state that is configured as a set of one or more qubits. The hardwired quantum logic circuits may be arranged as a set of processing engines, each processing engine being formed of a subset of the hardwired quantum logic circuits to perform one or more steps in the bioinformatics analysis on the reads of genomic data. Each subset of the hardwired quantum logic circuits may be formed in a wired configuration to perform the one or more steps in the bioinformatics analysis.

An apparatus for automatic detection of the face in a given image and localization of the eye region which is a target for recognizing iris is provided. The apparatus includes an image capturing unit collecting an image of a user; and a control unit extracting a characteristic vector from the image of the user, fitting an extracted vector into a Pseudo 2D Hidden Markov Model (HMM), and an operating method thereof for detecting a face and facial features of the user.