Abstract: A current collector, an electrochemical device containing the current collector, and an electronic device. The current collector includes a polymer substrate material and a conductive material. An electron resistivity of the current collector in an X-Y in-plane direction is 10 ?·cm to 1000 ?·cm, and an electron resistivity of the current collector in a Z direction is 0.01 ?·cm to 30 ?·cm. The current collector according to this application is excellent in oxidation resistance, reduction resistance, ionic insulation, mechanical strength, thermal stability, increases the energy density of bipolar electrochemical devices, and is more cost-effective and more suitable for mass production.

Abstract: A partition plate includes a partition substrate, a positive electrode membrane, a negative electrode membrane, and an insulation layer. The positive electrode membrane and the negative electrode membrane are respectively located on two surfaces of the partition substrate. The insulation layer is disposed on the partition substrate and the insulation layer is disposed at a periphery of the positive electrode membrane. A zone surrounded by orthographic projection of an outer edge of the insulation layer on the partition substrate covers orthographic projection of the negative electrode membrane on the partition substrate. This application can improve self-discharge and safety performances of electrochemical apparatuses.

Abstract: Data augmentation is described to train an artificial intelligence model that includes analyzing a first data set to measure an amount of data in the data set and the variation in the amount of data in the first data set to determine deficiencies for training an artificial intelligence model. Augmenting data is added for the first data set having an amount of data measured that fails to meet a threshold value. Deficiencies in the variation in the amount of data in the first data set are augmented using augmentation methods outside the variation scope of the first data set to provide a second data set of augmented data. An artificial intelligence model is trained with a combined data set of the first data set, and the second data set of augmented data when the first and second data set have an amount of data meeting the threshold value.

Abstract: A well log is scanned for one or more dimensions that describe one or more features of a well. Each dimension includes a plurality of values in a numerical format that represents each dimension. A missing value is detected in a first plurality of values of a first dimension of the well log. The first dimension of the well log is transformed, in response to the missing value, into a first image that visually depicts the first dimension including the first plurality of values and the missing value. Based on the first image and based on an image analysis algorithm a second image is created that visually depicts the first plurality of values and includes a found depiction visually depicting a found value in place of the missing value. The found depiction is converted, based on the second image, into a first value in the numerical format.

Abstract: An approach is provided for adaptively compressing a deep learning model. An original deep learning model for different Internet of Things (IoT) devices is determined. Device information is collected from the IoT devices. Based on the device information, multiple recommendation engines are selected from a set of recommendation engines. Compression factor combinations are determined by using the multiple recommendation engines. Compression ratios and model accuracies for the compression factor combinations are determined. Based on the compression ratios and the model accuracies, an optimal compression factor combination is selected from the compression factor combinations. A compressed deep learning model is generated by compressing the original deep learning model by using the optimal compression factor. The compressed deep learning model is deployed to the IoT devices.

Abstract: A system and method for adaptive color assignments to image labels during annotation of datasets includes preparing a dataset for image labeling by an annotator by: leveraging a global color analyzer to perform a global color distribution of a plurality of images to identify one or more overall colors present in the plurality of images, and a local color analyzer to perform a local color distribution for each image to identify one or more colors present in an area of interest of the image, and selecting a plurality of candidate colors to be used as image labels by the annotator, based on an output of the global color analyzer and an output of the local color analyzer.

Abstract: A computer-implemented method for annotating images is disclosed. The computer-implemented method includes generating a saliency map corresponding to an input image, wherein the input image is an image that requires annotation, generating a behavior saliency map, wherein the behavior saliency map is a saliency map formed from an average of a plurality of objects contained within respective bounding boxes of a plurality of sample images, generating a historical saliency map, wherein the historical saliency map is a saliency map formed from an average of a plurality of tagged objects in the plurality of sample images, fusing the saliency map corresponding to the input image, the behavior saliency map, and the historical saliency map to form a fused saliency map, and generating, based on the fused saliency map, a bounding box around an object in the input image.

Abstract: A system, method, and computer program product for implementing deep learning software model modification is provided. The method includes monitoring operational performance of a software model. An expected confidence level associated with the operational performance is first determined and it is determined that an inference associated with the expected confidence level is below a selected range of inferences associated with assigning new feature data as candidate video data. A candidate sequence comprising video data associated with the candidate video data is received and a similarity between frames of the candidate sequence is determined. A frame comprising a highest similarity with respect to segments of candidate video data is selected and it is detected that the frame is not associated with additional frames stored within a full cache structure. The software model is retrained such that the operational performance is modified.

Abstract: A method, system and computer program product for speech recognition using multiple languages includes receiving, by one or more processors, an input from a user, the input includes a sentence in a first language. The one or more processors translate the sentence to a plurality of languages different than the first language, and create vectors associated with the plurality of languages, each vector includes a representation of the sentence in each of the plurality of languages. The one or more processors calculate eigenvectors for each vector associated with a language in the plurality of languages, and based on the calculated eigenvectors, a score is assigned to each of the plurality of languages according to a relevance for determining a meaning of the sentence.

Abstract: A system, method, and computer program product for implementing video action recognition is provided. The method includes receiving a video stream comprising user movement actions. Skeleton points associated with a video representation of a user executing the user movement actions are extracted and categorized with respect to multiple digital levels. Initial visual windows points are generated within video frames and an average movement distance for the group of skeleton points are determined with respect to the video frames. In response, sizes for the visual windows are adjusted and feature vectors are extracted from the group of skeleton points. Point coordinates of the skeleton points are extracted and linked with the feature vectors. A convolutional neural network associated with linking the feature vectors with the point coordinates is generated and the video stream is enabled with respect to video action recognition associated with accurate presentation of the video stream.

Abstract: Embodiments of the present invention relate to methods, systems, and computer program products for managing a plurality of live comments. A plurality of live comments is obtained for a video, the plurality of live comments being associated with a plurality of fragments in the video, respectively. A plurality of features are extracted from the plurality of live comments, respectively. A knowledge base is generated for the plurality of live comments based on the plurality of features. With these embodiments, the live comments may be managed in an effective way. Further, the knowledge base may provide answers to a user query.

Abstract: A set of candidate intent vectors is generated from an input intent vector. A validation of the set of candidate intent vectors is performed that selects as valid intent vectors any of the set of candidate intent vectors that are semantically similar to the input intent vector.

Abstract: A method, a computing system and a computer program product for collecting and labelling images includes capturing a video of an object with a camera. A movement trace of a pointer is recorded that outlines the object while capturing the video of the object. Further included is generating a labeled image based at least on the captured video of the object and the recorded movement trace of the pointer. The labeled image includes the object and a line that surrounds the object.

Abstract: In an approach to deploying parallelizable deep learning models by adapting to the computing devices, a deep learning model is split into a plurality of slices, where each slice can exchange data with related slices. Virtual models are created from the plurality of slices, where the virtual models are based on capabilities of a plurality of devices on which the one or more virtual models are to be deployed, and further where each virtual model contains each slice of the plurality of slices. The one or more virtual models are stored in a cache. Responsive to determining that the deep learning model is to be deployed on one or more devices, a candidate model is selected from the virtual models in the cache, where the selection is based on information from a device monitor about the devices.

Abstract: Methods, computer program products, and/or systems are provided that perform the following operations: obtaining video data; dividing the video data into a plurality of video fragments based, at least in part, on page detection; extracting one or more elements from each of the plurality of video fragments; determining element type data for each of one or more extracted elements; generating element style data for the one or more extracted elements; determining page flow for the plurality of video fragments; and generating one or more pages based, at least in part, on the one or more elements extracted from the plurality of video fragments, the element type data, the element style data, and the page flow.

Abstract: A computer-implemented method for annotating images is disclosed. The computer-implemented method includes generating a saliency map corresponding to an input image, wherein the input image is an image that requires annotation, generating a behavior saliency map, wherein the behavior saliency map is a saliency map formed from an average of a plurality of objects contained within respective bounding boxes of a plurality of sample images, generating a historical saliency map, wherein the historical saliency map is a saliency map formed from an average of a plurality of tagged objects in the plurality of sample images, fusing the saliency map corresponding to the input image, the behavior saliency map, and the historical saliency map to form a fused saliency map, and generating, based on the fused saliency map, a bounding box around an object in the input image.

Abstract: The invention discloses an in situ polymerized flame retardant, derived from the following monomers: a diacid monomer A: where A1 is terephthalic acid, A2 is a phosphorus aromatic ring-containing reactive flame-retardant diacid monomer, A1+A2=100 mol %, A1=50 to 90 mol %, A2=10 to 50 mol %; and a diamine monomer B: one or more of diamine monomers containing 4 to 36 carbon atoms. In the present invention, a novel flame retardant is obtained by in situ polymerization of the phosphorus aromatic ring-containing reactive flame-retardant diacid monomers in semi-aromatic polyamide oligomers, which has advantages of no precipitation in the semi-aromatic polyamide and no influence on other properties of the semi-aromatic polyamide and has an excellent flame-retardant property.

Abstract: The invention discloses a flame-retardant semi-aromatic polyamide derived from the following monomers: a diacid monomer A: where A1 is terephthalic acid or terephthalic acid and other diacid, terephthalic acid accounts for 50 to 100 mol % of A1, and A2 is [(6-oxido-6H-dibenzo-(c,e)(1,2)-oxaphosphorin-6-ketone)-methyl]-butanedioic acid, A1+A2=100 mol %, A1=90 to 99 mol %, A2=1 to 10 mol %; and diamine monomer B: one or more of diamine monomers containing 4 to 36 carbon atoms. In the present invention, by an in situ polymerization, a specific flame-retardant monomer [(6-oxido-6H-dibenzo-(c,e)(1,2)-oxaphosphorin-6-ketone)-methyl]-butanedioic acid is copolymerized in a semi-aromatic polyamide chain segment, excellent mechanical properties and low water absorption can be obtained.

Abstract: An electrochemical device including a bipolar current collector. The bipolar current collector is hermetically connected to an outer package. Cavities independent of each other are formed on two opposite sides of the bipolar current collector. Each cavity contains an electrode assembly and an electrolytic solution. An electrode active material is disposed on at least one surface of the bipolar current collector. Adjacent electrode assemblies are connected in series. The electrochemical device according to this application not only improves the safety of the electrochemical device, but the electrode active material on the surface of the bipolar current collector also participates in a reaction process in the electrochemical device, so that the electrochemical device achieves both a high-voltage output and a relatively high energy density.

Abstract: A partition plate for use in an electrochemical device, an electrochemical device, and an electronic device are disclosed. The partition plate for use in an electrochemical device is ion-insulative and includes an intermediate layer and a sealing layer. The sealing layer is located on an upper surface and a lower surface of the intermediate layer. A material of the intermediate layer includes at least one of a carbon material, a first polymer material, or a metal material. A material of the sealing layer includes a second polymer material. A temperature at which the sealing layer starts to soften is at least 10° C. lower than a temperature at which the intermediate layer starts to soften. Three layers of superimposed composite films ensure ion insulation and sealing reliability.