Abstract: A method for a passive single-viewpoint 3D imaging system comprises capturing an image from a camera having one or more phase masks. The method further includes using a reconstruction algorithm, for estimation of a 3D or depth image.

Abstract: Disclosed herein is a system and method of identifying misplaced products on a retail shelf using a feature extractor trained to extract features from images of products on the shelf and output identifying information regarding the product in the product image. The extracted features are compared to extracted features in a product library and a best fit is obtained. A misplaced product is identified if the identifying information produced by the feature extractor fails to match the identifying information associated with the best fit features from the product library.

Abstract: A method and apparatus for establishing a software root of trust (RoT) ensures that the state of an untrusted computer system contains all and only content chosen by an external verifier and the system code begins execution in that state, or that the verifier discovers the existence of unaccounted for content. The method enables program booting into computer system states that are free of persistent malware such that an adversary cannot retain undetected control of an untrusted system.

Abstract: Electrochemical devices, and associated materials and methods, are generally described. In some embodiments, an electrochemical device comprises an electroactive material. The electroactive material may comprise an alloy having a solid phase and a liquid phase that co-exist with each other. As a result, such a composite electrode may have, in some cases, the mechanical softness to permit both high energy densities and an improved current density as compared to, for example, a substantially pure metal electrode.

Abstract: Provided herein are materials and methods that include utilizing atom transfer radical polymerization (ATRP) initiator molecules that maintain a positive charge during biomacro-initiator synthesis.

Abstract: Provided herein are systems, methods, and computer program products using tumor phylogeny, mutation rates, and machine learning to produce a clinical projection, such as patient survival, risk of malignancy, and therapeutic options. The method includes generating sequence variation data that identifies, characterizes, or quantifies at least one mutation in tumor sequence data of a tumor of a patient. The method also includes generating a phylogenic tree depicting clonal evolution of cells in the tumor of the patient. The method further includes determining at least one feature of the phylogenic tree including at least one value quantifying rates of mutation and/or at least one value representing at least one aspect of a structure of the phylogenic tree. The method further includes training a machine learning model to be configured to generate a projection for the patient comprising a clinical outcome or disease progression.

Abstract: A method of forming a microneedle array can include forming a sheet of material having a plurality of layers and micromilling the sheet of material to form a microneedle array. At least one of the plurality of layers can include a bioactive component, and the microneedle array can include a base portion and plurality of microneedles extending from the base portion.

Abstract: An intelligent, autonomous interior cleaning robot capable of autonomously mapping and cleaning multiple rooms in a house in an intelligent manner is described. Various combinations of passive and active sensors may be used to perform mapping, localization, and obstacle avoidance. In particular, the robot uses stereo cameras with a static projected light pattern to generate 3D data. In addition, the robot may use optical sensors in various locations, laser ToF sensors, inertial measurement units and visual odometry to enhance the localization and mapping capabilities.

Abstract: A computer implemented method for controlling a load aggregator for a grid includes receiving a predicted power demand over a horizon of time steps associated with one of at least two buildings, aggregating the predicted power demand at each time step to obtain an aggregate power demand, applying a learnable convolutional filter on the aggregate power demand to obtain a target load, computing a difference between the predicted power demand of the one building with the target load to obtain a power shift associated with the one building over the horizon of time steps, apportioning the power shift according to a learnable weighted vector to obtain an apportioned power shift, optimizing the learnable weighted vector and the learnable convolutional filter via an evolutionary strategy based update to obtain an optimized apportioned power shift, and transmitting the optimized apportioned power shift to a building level controller associated with the one building.

Abstract: Disclosed herein is an improved few-shot detector which utilizes semantic relation reasoning to learn novel objects from both visual information and the semantic relation of base class objects Specifically, a semantic space is constructed using word embeddings. Guided by the word embeddings of the classes, the detector is trained to project the objects from the visual space to the semantic space and to align their image representations with the corresponding class embeddings.

Abstract: Provided is a system and method for heating an item in a microwave oven. The method includes capturing, with at least one electromagnetic field sensor, at least one electromagnetic field measurement of a microwave chamber, each electromagnetic field measurement of the at least one electromagnetic field measurement corresponding to a region in the microwave chamber, generating an electromagnetic field map of the microwave chamber based on the at least one electromagnetic field measurement, capturing, with at least one sensor, a plurality of thermal measurements of the item being heated in the microwave chamber, each thermal measurement of the plurality of thermal measurements corresponding to a region on the item, and controlling at least one of a position of the item and the electromagnetic field while the item is being heated in the microwave chamber based on the electromagnetic field map and the plurality of thermal measurements.

Abstract: Disclosed herein are methods and apparatus for the imaging of brain electrical activity from electromagnetic measurements, using deep learning neural networks where a simulation process is designed to model realistic brain activation and electromagnetic signals to train generalizable neural networks and a residual convolutional neural network and/or a recurrent neural network is trained using the simulated data, capable of estimating source distributions from electromagnetic measurements, and their temporal dynamics over time, for pathological signals in diseased brains, such as interictal activity and ictal signals, and physiological brain signals such as evoked brain responses and spontaneous brain activity.

Abstract: A method for the efficient management of a fleet of electric vehicles in a target area couples vehicle dynamics and battery dynamics modeling with environmental factors to accurately incorporate the impact that the environment has on the range of the battery into the placement of the chargers by simulating trips of fleets of electric vehicles. The vehicles can be of various types, for example, motorcycles, cars, trucks or aircraft, and will each have their battery state of charge monitored as they traverse a simulated trip through the target area.

Abstract: An accessory optic is described which enables a non-immersed, long working distance microscope objective to be used as a higher-power immersion objective. This is particularly useful for biological imaging of specimens in an index-matching clarification medium. The accessory approach is the opposite of conventional unitized immersion objective design and presents several advantages over conventional design. The front lens element of the accessory may be selected to have precisely the refractive index of the specimen immersion medium and the accessory may be designed for use with immersion media that are incompatible with conventional immersion objectives. A dual accessory enables two such modified objectives to be optimized for light-sheet microscopy.

Abstract: A method of generating virtual sensor data of a virtual single-photon avalanche diode (SPAD) lidar sensor includes generating a two-dimensional (2D) lidar array having a plurality of cells. The method further includes interpolating image data from a virtual camera with the 2D lidar array to define auxiliary image data, generating a virtual ambient image based on a red-channel (R-channel) data of the auxiliary image data, identifying a plurality of virtual echoes of the virtual SPAD lidar sensor based on the R-channel data and a defined photon threshold, defining a virtual point cloud indicative of virtual photon measurements of the virtual SPAD lidar sensor based on the plurality of virtual echoes, and outputting data indicative of the virtual ambient image, the virtual photon measurements, the virtual point cloud, or a combination thereof, as the virtual sensor data of the virtual SPAD lidar sensor.

Abstract: Provided is a system, method, and computer program product for tracking a needle. The method includes determining a visibility of the needle being inserted into a subject in an image of a sequence of images, in response to determining that the visibility satisfies a visibility threshold, detecting a location of the needle based on at least one first algorithm and a detected curvature of the needle, in response to determining that the visibility does not satisfy the visibility threshold, detecting the location of the needle being inserted based on at least one second algorithm, and tracking the location of the needle in the sequence of images based on locations detected with the at least one first algorithm and the at least one second algorithm.

Abstract: Provided is a system, method, and computer program product for determining a needle injection site. The method includes segmenting, with at least one computing device, an image of a sequence of images into at least one object based on a machine-learning model configured to estimate its uncertainty for each segmentation, generating, with the at least one computing device, a 3D model of the at least one object, and determining, with the at least one computing device, an insertion location of the at least one object based at least partially on an output of the machine-learning model.

Abstract: The invention proposes a method of training a convolutional neural network in which, at each convolutional layer, weights for one seed convolutional filter per layer are updated during each training iteration. All other convolutional filters are polynomial transformations of the seed filter, or, alternatively, all response maps are polynomial transformations of the response map generated by the seed filter.

Abstract: A wearable device has a plurality of sensors surrounding a user's arm or wrist and provides depth information about the user's environment. Each sensor in the plurality of sensors has a field-of-view that may include the user's arm, torso, and surrounding environment. A controller receives data from the plurality of sensors and merges the data to create a composite image or depth point cloud. The device utilizes low-resolution sensors, with the composite image having a greater resolution and field-of-view than any individual sensor. The device is worn on the user's arm or wrist and can be used for static or continuous hand pose estimation, whole-arm pose estimation, and object detection, among other applications.

Abstract: A method to dynamically and adaptively sample the depths of a scene using the principle of triangulation light curtains is described. The approach directly detects the presence or absence of obstacles (or scene points) at specified 3D lines in a scene by sampling the scene. The scene can be sampled sparsely, non-uniformly, or densely at specified regions. The depth sampling can be varied in real-time, enabling quick object discovery or detailed exploration of areas of interest. Once an object is discovered in the scene, adaptive light curtains comprising dense sampling of a region of the scene containing the object, can be used to better define the position, shape and size of the discovered object.