International Business Machines Corporation

Rhodia Operations

Hon Hai Precision Industry Co., Ltd.

Boe Technology Group Co., Ltd.

Tsinghua University

Ordos Yuansheng Optoelectronics Co., Ltd.

Shanghai Xiaoyi Technology Co., Ltd.

Peng Ji

Ning Duan

Jian Ding

Zhi Hu Wang

Jing Chang Huang

Guo Qiang Hu

Peng Gao

Jun Zhu

Sheng Nan Zhu

Yuan Yuan Ding

Guoqiang Hu

Xiao Bo Li

JingChang Huang

Yu Zhang

Chun Ma

Fan Li

Qian Zhao

Jian Dong Ding

Lin Luo

Shun Xiang Yang

Yi Qi

Xinlin Wang

Vugranam Chakravarthy Sreedhar

Jun Chi Yan

Renjie Yao

Guotao Zhao

Wei Sun

Xin Zhang

Shao Chun Li

Wei Peng Huang

Qi Zhang

Timothy James Hahn

Jian Xu

Ren Jie Yao

Jiandong Ding

Guo-Fan Jin

Akira Nakamura

Lin Y Yang

Wei Zhao

Ya Bin Dang

Qian Ma

Yi Yang

Lei He

Jean-Christophe Castaing

Zhe Yan

Chang Jie Guo

Guan Zhang

Zhiyun Chen

Galder Cristobal

Jinfeng Li

Stéphane Streiff

Marie-Pierre Labeau

Alexander Lerch

Armin Liebens

Xuwei Li

Hongbin Lin

Da Ming Hao

Bing Hong

Bo Wen Wei

Wanghu Wu

Pingyu Tang

Ju Yuan

Feng-Lei Yang

Chang Chun Liu

A plurality of different images of a same region of interest in an object are input into a set of neural networks, wherein each image of the region has been captured under a different value of a variable condition. A classification for each image is generated by the set of neural networks, wherein each classification includes a confidence score in a prediction of whether a feature is present in the region. The image classifications are ensembled to generate a final classification for the region. By applying a loss function, a loss is computed based on comparing the final classification to a ground truth of whether the feature is present in the region. The parameters of the set of neural networks are adjusted based on the computed loss.

Feature detection based on neural networks

The present invention provides a method for increasing the growth of a plant by contacting a seed of the plant with a composition comprising a cationic guar having an average molecular weight of between 2,000 Daltons and 90,000 Daltons. The present invention also provides a seed treated with a cationic guar having an average molecular weight of between 2,000 Daltons and 90,000 Daltons.

Growth enhancement of plant by using cationic guars

Embodiments of the present invention facilitate product defect detection. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, a template image of a normal product; generating, by the device, one or more geometric training parameters for transforming the template image; and transforming, by the device, the template image using the one or more geometric training parameters to generate a transformed image for training a data model, wherein the trained data model being used for aligning the template image and an image under inspection of a product.

Product defect detection

In an approach to AI empowered factory automation using an industrial IoT, responsive to receiving a new production task, production requirements are input into an AI engine. Equipment and software containers are selected based on the AI model. An orchestration service is created, where the orchestration service collaborates the equipment and the software containers.

Artificial Intelligence empowered industrial Internet of Things

A system, method, and computer program product provides a way to separate connected or adhered adjacent characters of a digital image for license plate recognition. As a threshold processing, the method performs a recognition of character adhesion by obtaining character parameters using an image processor. The parameters include a horizontal max crossing and a ratio of width and height. A first rule-based module is used responsive to the character parameters to distinguish the adhered characters (character adhesions) that are easy to judge, leaving the uncertain part to a character adhesion classifier model for discrimination. Character adhesion data is obtained by data augmentation including the adding of a random distance between two single characters to create class like adhered characters. Then the character adhesion classifier model of single character and character adhesion data is trained. Any uncertain part can be distinguished by the trained character adhesion classifier model.

Character recognition of license plate under complex background

A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

Intelligent in-vehicle air-quality control

The present invention relates to a method, system and computer program product for defect enhancement. According to the method, a plurality of proposed regions from a plurality of images taken for a display panel is obtained. Each of proposed region of the plurality of proposed regions include a suspected defect on the display panel. At least two proposed regions from the plurality of proposed regions that deserve to be superimposed based on a set of conditions is determined. The at least two proposed regions for acquiring an enhanced defect are superimposed.

Display panel defect enhancement

Provided is the use of a lanthanide metal complex as a bleaching catalyst. In particular, the lanthanide metal complex comprises a ligand which is an aromatic compound having at least one electron withdrawing substituent and at least one nucleophilic group. Provided is also a composition containing the lanthanide metal complex.

Composition containing lanthanide metal complex

Blockchain based IoT data management can include receiving IoT data are with one or more processing units. At least one aggregation pattern of the IoT data can be determined by one or more processing units. The IoT data can be hashed, based upon the at least one aggregation pattern to obtain hash values of the IoT data by one or more processing units. The hash values can be sent to a blockchain system for storing by one or more processing units.

Blockchain based IOT data management

The present disclosure relates to training a machine learning model to classify images. An example method generally includes receiving a training data set including images in a first category and images in a second category. A convolutional neural network (CNN) is trained using the training data set, and a feature map is generated from layers of the CNN based on features of images in the training data set. A first area in the feature map including images in the first category and a second area in the feature map where images in the first category overlap with images in the second category are identified. The first category is split into a first subcategory corresponding to the first area and a second subcategory corresponding to the second area. The CNN is retrained based on the images in the first subcategory, images in the second subcategory, and images in the second category.

Classifying images in overlapping groups of images using convolutional neural networks

A method, a device and a computer program product for image processing are proposed. In the method, a first training image and region information are obtained. The region information indicates a region of a defect in the first training image. A second training image with the defect at least partially removed is generated using an image generator based on the first training image and the region information. The image generator is trained to recover the first training image by replacing pixels included in the region indicated by the region information. The image generator is updated based on the second training image. In this way, the image including the defect can be accurately and efficiently recovered.

Image recovery

Embodiments of the present disclosure provide a sintering device and a sintering method thereof. The sintering device includes: a housing, defining a chamber; and at least one first heating mechanism and at least one second heating mechanism, disposed in the chamber, wherein the at least one first heating mechanism and the at least one second heating mechanism provide different heating temperatures for a workpiece to be processed.

Sintering device and sintering method thereof

A method and an apparatus for generating a road network are disclosed. The method for generating a road network comprises: aggregating a plurality of grid cells partitioned in advance on a trajectory map based on trajectories in each grid cell of the plurality of grid cells to form level-1 regions; and generating a link of the road network by merging a level-1 region having two valid neighbors with its neighbor level-1 regions having two valid neighbors.

Road network generation

Methods, systems and computer program products for providing improved visualization of inspection results are provided. Aspects include receiving an image from a connected camera by a computing device and processing the image by a graphics processing unit to divide the image into a plurality of image blocks. Responsive to inputting the processed image into a trained model, a plurality of image areas within the processed image is identified. Each image area is associated with an importance level and includes a unique set of image blocks. A sequence of image blocks is determined based on an importance level associated with each of the plurality of image blocks, wherein the sequence includes a list of image blocks in descending order by the importance level of each image block. The image blocks are stored in order of the sequence of image blocks by the server.

Visualization of inspection results

Techniques are provided for blockchain based a data transformation. According to one aspect, a series of Internet of Things (IoT) data is received by one or more processing units. And at least one reference data set to the received series of IoT data are attached by one or more processing units. The received series of IoT data attached are processed, by one or more processing units, with at least one transformation module to obtain a processing result of the at least one reference data set. A hash value of the processing result is calculated by one or more processing units. The hash value of the processing result and a hash value of an expected result stored in a blockchain system are compared. In respond to the hash value of the processing result being not matched with the hash value of the expected result, the decision of the at least one transformation module having been tampered with is determined by one or more processing units.

Blockchain based data transformation

Growing community of inventors

Nanjing, China

Peng Ji