Huawei Technologies Co., Limited

Maplebear Inc.

Tyco Electronics (shanghai) Co., Ltd.

Covidien LP

Leica Microsystems Ltd., Shanghai

Intel Corporation

Te Connectivity Corporation

Te Connectivity Germany Gmbh

Tongji University

Tyco Electronics Technology (sip) Ltd.

Tyco Electronics Technology (sip) Co. Ltd.

Tyco Electronics (sip) Co. Ltd.

Tyco Electronics Co., Ltd.

Xiao Zhou

Yilin Huang

Shiyuan Yang

Xin Luo

Zui Tao

Ganglu Wu

Michael Kadichevitz

Jie Zhao

Youming Luo

Yi Chen

Doron Ezri

Qi Wang

Avi Weitzman

Wentao Pan

Qunwei Liu

Jifa Wang

Bo Yuan

Xingfeng Jiang

Lin Gao

Zheguang Fan

Yuping Shu

Yu Zhang

Yiliang Wu

Anbang Yao

Jun Zhang

Hao Wu

Helge Schmidt

Tao Tao

Haomai Yin

Yuchen Yang

Soenke Sachs

Hui Zhan

Ziwei Li

Shuguang Xiao

Ahmed Beshry

Kun Zhang

Felix Greiner

Guangli Zhang

Hexiang Yan

Lan Chang

Dian Gu

Shuping Li

Cancan Zhao

Kunlun Xin

Weirong Xu

Shallu Soneja

Yufeng He

Gokce Gulsoy

Isabel Tsai

Griffin Kelly

Elison Wang

Alexander Ginsburg

Techniques related to poly-scale kernel-wise convolutional neural network layers are discussed. A poly-scale kernel-wise convolutional neural network layer is applied to an input volume to generate an output volume and include filters each having a number of filter kernels with the same sample rate and differing dilation rates optionally in a repeating pattern of dilation rate groups within each of filters with the pattern of dilation rate groups offset between the filters the poly-scale kernel-wise convolutional neural network layer.

Poly-scale kernel-wise convolution for high-performance visual recognition applications

A barcode decoding system decodes item identifiers from images of barcodes. The barcode decoding system receives an image of a barcode and rotates the image to a pre-determined orientation. The barcode decoding system also may segment the barcode image to emphasize the portions of the image that correspond to the barcode. The barcode decoding system generates a binary sequence representation of the item identifier encoded in the barcode by applying a barcode classifier model to the barcode image, and decodes the item identifier from the barcode based on the binary sequence representation.

Image-based barcode decoding

An automated checkout system modifies received images of machine-readable labels to improve the performance of a label detection model that the system uses to decode item identifiers encoded in the machine-readable labels. For example, the automated checkout system may transform subregions of an image of a machine-readable label to adjust for distortions in the image's depiction of the machine-readable label. Similarly, the automated checkout system may identify readable regions within received images of machine-readable labels and apply a label detection model to those readable regions. By modifying received images of machine-readable labels, these techniques improve on existing computer-vision technologies by allowing for the effective decoding of machine-readable labels based on real-world images using relatively clean training data.

Subregion transformation for label decoding by an automated checkout system

An online concierge system may use images received from shopping carts within retailers to determine the availability of items within those retailers. A shopping cart includes externally-facing cameras that automatically capture images of the area around the shopping cart as the shopping cart travels through a retailer. The online concierge system receives these images, which depict displays within the retailers from which a picker or a retailer patron can collect items. The online concierge system determines which items should be depicted in the images and which items are actually depicted in the images. The online concierge system identifies which items should be depicted, but are not depicted, and determines that these items are unavailable (e.g., out of stock) at that retailer. The online concierge system updates an availability database to indicate that these items are unavailable and may notify the retailer that the item is unavailable.

Cart-based availability determination for an online concierge system

An antenna assembly includes N elements, a feeding network, and a printed circuit board (PCB). N is an integer greater than or equal to 3. The N elements and the feeding network are located on the PCB. The N elements are all connected to the feeding network, each element has a radial part, the radial part of each element points to an antenna phase center, and a length of the radial part of each element is greater than a sum of lengths of other non-radial parts.

Antenna assembly and wireless device

Self-checkout vehicle systems and methods comprising a self-checkout vehicle having a camera(s), a weight sensor(s), and a processor configured to: (i) identify via computer vision a merchandise item selected by a shopper based on an identifier affixed to the selected item, and (ii) calculate a price of the merchandise item based on the identification and weight of the selected item. Computer vision systems and methods for identifying merchandise selected by a shopper comprising a processor configured to: (i) identify an identifier affixed to the selected merchandise and an item category of the selected merchandise, and (ii) compare the identifier and item category identified in each respective image to determine the most likely identification of the merchandise.

Systems and methods for item recognition

An antenna for a wireless communication device, such as a Wi-Fi access point is provided. The antenna includes an electrically conductive radiation structure including a plurality of radially extending radiation slots, each of which has an open outer end at a perimeter of the electrically conductive radiation structure and defines a respective radiation portion of the electrically conductive radiation structure. The antenna includes a feeding network configured to feed an RF signal to the electrically conductive radiation structure, the feeding network includes a plurality of feeding arms configured to feed the RF signal into each radiation portion of the electrically conductive radiation structure for exciting each radiation portion to emit electromagnetic waves. The antenna includes a grounding structure including an electrically conductive grounding surface, which is spaced from and faces each radiation portion of the electrically conductive radiation structure for guiding the electromagnetic waves emitted by each radiation portion.

Antenna for a wireless communication device and such a device

A smart shopping cart includes internally facing cameras and an integrated scale to identify objects that are placed in the cart. To avoid unnecessary processing of images that are irrelevant, and thereby save battery life, the cart uses the scale to detect when an object is placed in the cart. The cart obtains images from a cache and sends those to an object detection machine learning model. The cart captures and sends a load curve as input to the trained model for object detection. Labeled load data and labeled image data are used by a model training system to train the machine learning model to identify an item when it is added to the shopping cart. The shopping cart also uses weight data and the image data from a timeframe associated with the addition of the item to the cart as inputs.

Training a model to identify items based on image data and load curve data

A shipping cover for a staple cartridge includes a body having an upper surface and a lower surface that is in close opposition to the staple cartridge when the shipping cover is secured to the staple cartridge. The shipping cover includes a latch that is received within a body of the staple cartridge to secure the shipping cover to the cartridge body. The latch is manually movable by a clinician to facilitate removal of the shipping cover from the staple cartridge.

Shipping cover for staple cartridge

An antenna device includes a plurality of dipole antennas and a port. Each of the dipole antennas is connected to the port. The plurality of dipole antennas is arranged around the port. Each of the plurality of dipole antennas includes two ends. The ends of the dipole antennas are arranged in a plurality of pairs. Each pair includes one end of one of the dipole antennas and one end of another one of the dipole antennas. The two ends in each pair are arranged in proximity to each other. One or more switches are configured to switch between (1) an omnidirectional state, in which the ends of the dipole antennas are not connected to each other; and (2) a directional state, in which the two ends in each of one or more of the pairs are connected to each other.

Beam diversity by smart antenna without passive elements

A reconfigurable antenna includes a bottom plate, a vertically polarized high-density antenna, and a controllable reflector. The controllable reflector is located between the bottom plate and the vertically polarized high-density antenna, and a projection of the controllable reflector on the bottom plate is at a center of a projection of the vertically polarized high-density antenna on the bottom plate. The controllable reflector includes a switch, and the switch is configured to enable the controllable reflector to be in an operating state or an off state.

Reconfigurable antenna and network device

An antenna has a reflector and an active element. The reflector includes a multi-segment metal structure having a length within a first value range. The multi-segment metal structure includes a first metal structure connected to a second metal structure. A PIN diode is disposed on the first metal structure. The first metal structure is parallel to a polarization direction of the active element. The second metal structure is perpendicular to the first metal structure.

Antenna and wireless device

Growing community of inventors

Shanghai, China

Xiao Zhou