Abstract: A bracket for a display assembly includes a body that has a first edge and a second edge that define a first surface and a second surface of the body. An elongated retention feature is coupled to the first edge of the body and defines an elongated slot proximate to the first surface of the body. A plurality of retention clips are coupled to the second edge of the body. Each of the plurality of retention clips define a slot proximate to the first surface of the body. At least one housing is coupled to the second surface of the body and defines locking apertures. At least one cap is selectively coupled to the at least one housing. The at least one cap defines locking features selectively disposed within the locking apertures that are defined by the at least one housing.

Abstract: An image coding method includes: writing, into a sequence parameter set, buffer description defining information for defining a plurality of buffer descriptions; writing, into the sequence parameter set, reference list description defining information for defining a plurality of reference list descriptions corresponding to the buffer descriptions; and writing, into a first header of each processing unit which is included in a coded bitstream, buffer description selecting information for specifying a selected buffer description.

Abstract: The present invention discloses a data scheduling register tree structure for radix-2 FFT architecture. The operation method of the proposed invention, there is no need for the Random Access Memory (RAM) to store the data; instead, shift registers with some multiplexers are enough to perform the memory operation with less hardware. There are three steps in the FFT computation such as input storage, data processing and output retrieval. The data processing step is further configured in four different operations. The number of operation mainly depends upon the size of the FFT, which is equal to log2N modes. During each operation, the DSRT changes its structure and these structures are basically MDC (Multi-path Delay Commutator) structures.

Abstract: A device for use with a vehicle-mounted image acquisition unit includes a main body. The main body includes a first end and a second end opposite to the first end. The main body further defines an interior cavity extending between the first end and the second end, and a plurality of apertures therethrough between the first end and the second end. The first end of the main body is configured to be disposed at or near the vehicle-mounted image acquisition unit. The vehicle-mounted image acquisition unit has a field of view extending through the interior cavity and through the second end to an outside environment surrounding a vehicle.

Abstract: Poses of a person depicted within video frame may be determined. The poses of the person may be used to generate intermediate video frames between the video frames.

Abstract: There is disclosed a viewing system coupled to a motor vehicle having a frame having a roof, at least one support, and a body with the at least one support supporting the roof over the body. The system can comprise at least one camera, at least one screen coupled to the support. In addition each camera is coupled to the at least one support and wherein said at least one screen is in communication with the first set of cameras, wherein said at least one screen displays images presented by the first set of cameras. This device can provide additional view in the blind spot of the vehicle.

Abstract: A terminal number estimating system includes: a plurality of receivers that receive a wireless signal transmitted from a plurality of terminal devices by frequency-division multiple access; a Fourier transform unit that performs a discrete Fourier transform on each wireless signal received by the plurality of reception means and outputs a discrete Fourier coefficient; and a terminal number estimation unit that estimates a position of each terminal device by clustering a resource block of each wireless signal based on each discrete Fourier coefficient.

Abstract: A kit (10) includes a light source (12) and an optical system (14) equipped with a lens assembly (25) defining a magnification optical axis (X-X). A frame (16) is crossable by the light generated by the light source (12). The frame (16) is configured for supporting a sample holder (H), a portable electronic apparatus (S) equipped with an image acquisition device (C), and the optical system (14), which are interposable between the sample holder (H) and the image acquisition device (C). The optical system (14) is configured for being movable in a guided manner on the frame (16), to allow aligning the optical axis (X-X) with the image acquisition device (C). A carrying body (18) is configured for receiving in abutment the frame (16) and housing the light source (12) directing light towards the optical system (14) through the frame (16).

Abstract: An apparatus, method and computer program is described comprising detecting a first object in a first image of a sequence of images using a neural network (22), wherein the means for detecting the first object provides an object area indicative of a first location of the first object; and tracking the first object (24), wherein the means for tracking the first object further comprises generating a predicted future location of the first object and generating an updated location of the first object using the neural network. The means for generating the predicted future location of the first object may, for example, receive said object area indicative of a first location of the first object and may receive said updated location information of the first object.

Abstract: An imaging flow cytometer device includes a housing holding a multi-color illumination source configured for pulsed or continuous wave operation. A microfluidic channel is disposed in the housing and is fluidically coupled to a source of fluid containing objects that flow through the microfluidic channel. A color image sensor is disposed adjacent to the microfluidic channel and receives light from the illumination source that passes through the microfluidic channel. The image sensor captures image frames containing raw hologram images of the moving objects passing through the microfluidic channel. The image frames are subject to image processing to reconstruct phase and/or intensity images of the moving objects for each color. The reconstructed phase and/or intensity images are then input to a trained deep neural network that outputs a phase recovered image of the moving objects. The trained deep neural network may also be trained to classify object types.

Abstract: A control system for automatic operation of a coker, the control system. The control system includes a drum feeder operable to modulate a feed of oil into a coke drum of the coker. The control system further includes a controller with a processing circuit. The processing circuit obtains a target coke rate indicating a target rate at which to accumulate coke within the coke drum. The processing circuit further uses a neural network model to generate a target coker feed rate predicted to result in the coke accumulating within the coke drum at the target coke rate. The target coker feed rate indicates a target rate at which to feed the oil into the coke drum. The processing circuit further operates the drum feeder using the target coker feed rate to modulate the feed of oil into the coke drum.

Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe

Abstract: Provided is an illumination control system including: an image capturing unit capturing an image in real time; a motion sensing unit sensing motion in the image and generating a notification; a communication unit receiving the image and the notification for transmission to outside, and receiving a control signal; a control unit receiving information on the image and the notification through the communication unit, analyzing the information, and transmitting the control signal for control; a light unit connected to the communication unit so that lights are controlled through the control signal; and a storage unit storing the information.

Abstract: The endoscope objective optical system includes in order from an object side, a first lens group having a positive refractive power, a second lens group having a negative refractive power, and a third lens group having a positive refractive power. A lens surface positioned nearest to an image side in the second lens group is a concave surface which is directed toward the image side. The second lens group moves along an optical axis.

Abstract: A method of multi-rate neural image compression with stackable nested model structures is performed by at least one processor and includes iteratively stacking, on a first prior set of weights of a first neural network corresponding to a prior hyperparameter, a first plurality of sets of weights of a first plurality of stackable neural networks corresponding to a current hyperparameter, wherein the first prior set of weights of the first neural network remains unchanged, encoding an input image to obtain an encoded representation, using the first prior set of weights of the first neural network on which the first plurality of sets of weights of the first plurality of stackable neural networks is stacked, and encoding the obtained encoded representation to determine a compressed representation.

Abstract: Methods and apparatuses are disclosed for recording video data of an event. The apparatuses include a processor communicating with memory. The memory stores video data of the event captured by a camera, and the video data includes a series of picture frames of the event. A loop buffer also stores video data of the event captured by the camera. A rule-based engine stored in the memory uses a set of rules to store the contents of the loop buffer in the memory. The apparatus utilizes the loop buffer to provide video data prior to occurrence of the event.

Abstract: A range Doppler angle detection method executed by a range Doppler angle detection device includes steps of: receiving a first sensing signal and a second sensing signal; performing 1D Fast Fourier Transform (FFT) and 2D FFT to the first sensing signal for calculating one first 2D FFT map; performing the 1D FFT and the 2D FFT to the second sensing signal for calculating one second 2D FFT map; picking up one column of the first 2D FFT map and one column of the second 2D FFT map according to a given Doppler index; performing the 3D FFT to the picked column of the first 2D FFT map and the picked column of the second 2D FFT map for calculating a range Doppler angle. Therefore, a computation loading of the gesture recognition function can be reduced.

Abstract: Systems and techniques are described herein for processing video data using a neural network system. For instance, a process can include generating, by a first convolutional layer of an encoder sub-network of the neural network system, output values associated with a luminance channel of a frame. The process can include generating, by a second convolutional layer of the encoder sub-network, output values associated with at least one chrominance channel of the frame. The process can include generating a combined representation of the frame by combining the output values associated with the luminance channel of the frame and the output values associated with the at least one chrominance channel of the frame. The process can include generating encoded video data based on the combined representation of the frame.

Abstract: Aspects of the disclosure provide methods, apparatuses, and a non-transitory computer-readable medium for point cloud compression and decompression. In a method, syntax information of a point cloud in a quantized space is decoded from a coded bitstream. The syntax information includes dividing information and adaptive geometry quantization information for a bounding box of the point cloud. The bounding box of the point cloud is divided into a plurality of parts based on the dividing information. Quantization parameters for the parts in the bounding box are determined based on the adaptive geometry quantization information. Points in each of the parts in the bounding box of the point cloud are reconstructed based on the quantization parameter for the respective part in the bounding box.

Abstract: A video decoding method according to the present disclosure may include determining whether an affine motion model is applied to a current block or not, performing motion compensation for the current block according to whether the affine motion model is applied or not, determining a value of a first variable and a second variable representing whether a prediction block obtained by the motion compensation will be refined and determining a padding size of the prediction block.