Abstract: Image processing apparatuses and systems implementing deep learning architectures that can learn high-quality representations of images (e.g., of real estate images of properties) are described. The described techniques may be implemented to generate high-quality image representations may be used for various downstream applications including improved image captioning applications, improved image labeling applications, improved image search applications, etc. For instance, image representations generated according to one or more aspects of the described techniques may be used for image (e.g., real estate/property) classification, automatic property listing generation based on one or more images, property or listing recommendations based on searched images, etc.

Abstract: Aspects of the invention include a computer-implemented method that includes generating an intermediate ECG vector representation and an intermediate optical sensor vector representation. The intermediate ECG vector representation and the intermediate optical sensor vector representation is translated to a joint representation in a vector space. The similarities detected between the electrocardiogram (ECG) data and optical sensor data from the joint vector space representation. Features that are indicative of an ischemic disease of a patient are extracted from the joint vector space representation based at least in part on the detected similarities. The ischemic disease of the patient is detected based at least in part on the extracted features.

Abstract: Systems and methods are described for efficiently meeting the needs of property buyers, sellers, and agents. Attributes of the user and of each property are combined and processed by a machine learning model. The output represents a prediction that a user will choose to view the property. Each property is ranked and displayed to the user. When the user selects a property, the interaction is used to update the machine learning model. In some cases, a natural language processing system identifies property and user attributes based on a natural language query. In some cases, a chatbot may respond to a natural language query in real time. The system may also be utilized to provide matching services for buyers or sellers to agents, or third party service providers, as well as matching buyers and sellers directly to each other, or user to other users for transaction, interaction and other needs.

Abstract: A method of monitoring cardiac health of a human (user) includes measuring back portion cardiac data using one or more sensors that are all in contact with a posterior of a human torso. The method further includes detecting a cardiac anomaly using machine learning based on the back portion cardiac data. In one or more examples, the method further includes converting the back portion cardiac data to front portion cardiac data using a translation model, wherein the front portion cardiac data is used for detecting the cardiac anomaly. In one or more examples, the one or more sensors are positioned using a panel that is incorporated into a garment that is in contact with the human torso. The panel can be detachable from the garment in one or more examples.

Abstract: Systems and methods are described for efficiently meeting the needs of property buyers, sellers, and agents. Attributes of the user and of each property are combined and processed by a machine learning model. The output represents a prediction that a user will choose to view the property. Each property is ranked and displayed to the user. When the user selects a property, the interaction is used to update the machine learning model. in some cases, a natural language processing system identifies property and user attributes based on a natural language query. In some cases, a chatbot may respond to a natural language query in real time. The system may also be utilized to provide matching services for buyers or sellers to agents, or third party service providers, as well as matching buyers and sellers directly to each other, or user to other users for transaction, interaction and other needs.