Abstract: A method and a system for recommending a target garment matching an inputted garment. The method includes: extracting attributes from text description and image of the inputted garment to obtain extracted attributes; querying a knowledge graph using the extracted attributes to obtain matched attributes; retrieving candidate products from a garment pool using the matched attributes; extracting features from the inputted garment and the candidate products; determining the target garment from the candidate products based on grading scores between the features of the inputted garment and the features of the candidate products; and recommending the target garment. The knowledge graph includes nodes corresponding to type of clothes, category of clothes, attribute keys, values of attribute keys, context keys, values of context keys, combination of the values of the attribute keys and the type of clothes, and combination of the value of the attribute keys and the category of clothes.

Abstract: A photonic chip and a preparation method thereof are provided. The chip includes a lithium niobate film modulator array, a first optical coupling array, and a silica waveguide wavelength-division multiplexer, and the lithium niobate film modulator array includes one or more lithium niobate film modulators and is used to modulate an optical signal; the first optical coupling array includes one or more first optical coupling structures, and the first optical coupling structure has one end connected to a corresponding lithium niobate thin film modulator and the other end connected to the silica waveguide wavelength-division multiplexer so as to transmit the modulated optical signal to the silica waveguide wavelength-division multiplexer; and the silica waveguide wavelength-division multiplexer is used to perform wavelength-division multiplexing on the modulated optical signal.

Abstract: A system and a method for training an inference model using a computing device. The method includes: providing a text-to-vector converter; providing the inference model and pre-training the inference model using labeled fashion entries; providing non-labeled fashion entries; separating each of the non-labeled fashion entries into a target image and target text; converting the target text into a category vector and an attribute vector using the text-to-vector converter; processing the target image using the inference model to obtain processed target image and target image label; comparing the category vector to the target image label; when the category vector matches the target image label, updating the target image label based on the category vector and the attribute vector to obtain updated label; and retraining the inference model using the processed target image and the updated label.

Abstract: An optical coupling structure, an optical coupling system and a method for preparing the optical coupling structure are provided. The method includes: step S101: preparing a base substrate; step S102: forming a lithium niobate optical waveguide on the base substrate; step S103: forming a silicon dioxide core layer enclosing the lithium niobate optical waveguide on peripheral walls of the lithium niobate optical waveguide; step S104: forming a silicon dioxide cladding layer enclosing the silicon dioxide core layer on peripheral walls of the silicon dioxide core layer. The optical coupling structure alleviates a technical problem of low coupling efficiency between the lithium niobate optical waveguide and the single-mode optical fiber in the related art, and achieves a technical effect of improving the coupling efficiency between the lithium niobate optical waveguide and the single-mode optical fiber.

Abstract: A system and a method for multimedia data analysis. The system includes a computing device. The computer device includes a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: encode task description and task meta info into concatenated task vectors; encode context text and context meta info into concatenated context text vectors; encode context image and the context meta info into concatenated context image vectors; perform dual coattention on the concatenated task vectors and the concatenated context text and image vectors to obtain attended task vectors and attended context vectors; perform BiLSTM on the attended task vectors and the attended context vectors to obtain task encoding and context encoding; and decode the task encoding and the context encoding to obtain an answer to the task.

Abstract: A photonic chip and a preparation method thereof are provided. The chip includes a lithium niobate film modulator array, a first optical coupling array, and a silica waveguide wavelength-division multiplexer, and the lithium niobate film modulator array includes one or more lithium niobate film modulators and is used to modulate an optical signal; the first optical coupling array includes one or more first optical coupling structures, and the first optical coupling structure has one end connected to a corresponding lithium niobate thin film modulator and the other end connected to the silica waveguide wavelength-division multiplexer so as to transmit the modulated optical signal to the silica waveguide wavelength-division multiplexer; and the silica waveguide wavelength-division multiplexer is used to perform wavelength-division multiplexing on the modulated optical signal.

Abstract: A method and a system for recommending a target garment matching an inputted garment. The method includes: extracting attributes from text description and image of the inputted garment to obtain extracted attributes; querying a knowledge graph using the extracted attributes to obtain matched attributes; retrieving candidate products from a garment pool using the matched attributes; extracting features from the inputted garment and the candidate products; determining the target garment from the candidate products based on grading scores between the features of the inputted garment and the features of the candidate products; and recommending the target garment. The knowledge graph includes nodes corresponding to type of clothes, category of clothes, attribute keys, values of attribute keys, context keys, values of context keys, combination of the values of the attribute keys and the type of clothes, and combination of the value of the attribute keys and the category of clothes.

Abstract: A method and system for generating a three-dimensional (3D) model of a garment. The method includes: providing an image of the garment; generating a 3D garment representation based on the image; registering the 3D garment representation to a 3D model to obtain a preliminary 3D garment model; projecting the preliminary 3D garment model dressed on the 3D model to an 2D projected image; and comparing the 2D projected image with the image of the garment, so as to refine the preliminary 3D garment model to obtain the final 3D model of the garment.

Abstract: An optical coupling structure, an optical coupling system and a method for preparing the optical coupling structure are provided. The method includes: step S101: preparing a base substrate; step S102: forming a lithium niobate optical waveguide on the base substrate; step S103: forming a silicon dioxide core layer enclosing the lithium niobate optical waveguide on peripheral walls of the lithium niobate optical waveguide; step S104: forming a silicon dioxide cladding layer enclosing the silicon dioxide core layer on peripheral walls of the silicon dioxide core layer. The optical coupling structure alleviates a technical problem of low coupling efficiency between the lithium niobate optical waveguide and the single-mode optical fiber in the related art, and achieves a technical effect of improving the coupling efficiency between the lithium niobate optical waveguide and the single-mode optical fiber.

Abstract: A system and a method for multimedia data analysis. The system includes a computing device. The computer device includes a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: encode task description and task meta info into concatenated task vectors; encode context text and context meta info into concatenated context text vectors; encode context image and the context meta info into concatenated context image vectors; perform dual coattention on the concatenated task vectors and the concatenated context text and image vectors to obtain attended task vectors and attended context vectors; perform BiLSTM on the attended task vectors and the attended context vectors to obtain task encoding and context encoding; and decode the task encoding and the context encoding to obtain an answer to the task.

Abstract: A method and system for monitoring an e-commerce platform using artificial intelligence and fixing malfunctions on the e-commerce platform. The method includes: receiving, by a computing device, a feedback submitted by a user through the e-commerce platform; generating a vector based on content of the feedback, context of the feedback and profile of the user using AI processors; and classifying the vector to determine function corresponding to the feedback and status of the function using AI classifiers. The content includes text, voice, image and video; the context includes time, location and submission channel of the feedback; the profile includes attributes, history and preference of the user. Dimensions of the vector respectively corresponding to the text, voice, image, video, time, location, submission channel, attributes, history, and preference of the user.

Abstract: A system and a method for training an inference model using a computing device. The method includes: providing a text-to-vector converter; providing the inference model and pre-training the inference model using labeled fashion entries; providing non-labeled fashion entries; separating each of the non-labeled fashion entries into a target image and target text; converting the target text into a category vector and an attribute vector using the text-to-vector converter; processing the target image using the inference model to obtain processed target image and target image label; comparing the category vector to the target image label; when the category vector matches the target image label, updating the target image label based on the category vector and the attribute vector to obtain updated label; and retraining the inference model using the processed target image and the updated label.

Abstract: A method and system for generating a three-dimensional (3D) model of a garment. The method includes: providing an image of the garment; generating a 3D garment representation based on the image; registering the 3D garment representation to a 3D model to obtain a preliminary 3D garment model; projecting the preliminary 3D garment model dressed on the 3D model to an 2D projected image; and comparing the 2D projected image with the image of the garment, so as to refine the preliminary 3D garment model to obtain the final 3D model of the garment.

Abstract: A method for simultaneous localization and mapping. The method includes the step of detecting two-dimensional (2D) feature points from a current frame captured by a camera; matching the 2D feature points from the current frame directly to three-dimensional (3D) map points in a 3D map, so as to obtain correspondence between the 2D feature points and the 3D map points; and computing a current pose of the camera based on the obtained correspondence. Each of the 2D feature points and the 3D map points has a feature descriptor. The step of matching is performed by comparing the feature descriptors of the 2D feature points and the feature descriptors of the 3D map points.

Abstract: A method and system for monitoring an e-commerce platform. The method includes: receiving, by a computing device, a feedback submitted by a user through the e-commerce platform; generating a vector based on content of the feedback, context of the feedback and profile of the user using AI processors; and classifying the vector to determine function corresponding to the feedback and status of the function using AI classifiers. The content includes text, voice, image and video; the context includes time, location and submission channel of the feedback; the profile includes attributes, history and preference of the user. Dimensions of the vector respectively corresponding to the text, voice, image, video, time, location, submission channel, attributes, history, and preference of the user.

Abstract: A method for simultaneous localization and mapping. The method includes the step of detecting two-dimensional (2D) feature points from a current frame captured by a camera; matching the 2D feature points from the current frame directly to three-dimensional (3D) map points in a 3D map, so as to obtain correspondence between the 2D feature points and the 3D map points; and computing a current pose of the camera based on the obtained correspondence. Each of the 2D feature points and the 3D map points has a feature descriptor. The step of matching is performed by comparing the feature descriptors of the 2D feature points and the feature descriptors of the 3D map points.

Abstract: Disclosed herein are a method and apparatus that adaptively perform encoding and decoding based on image quality. An encoding apparatus may determine optimal Frames Per Second (FPS) for a video and may encode the video based on the determined FPS. Further, the encoding apparatus may provide improved temporal scalability. A decoding apparatus may select a frame to be displayed from among frames of a video depending on a required minimum satisfied user ratio. Through the selection of the frame, the decoding apparatus may provide improved temporal scalability.

Abstract: A method for a user to select merchandise online for purchase, by: (a) the user uploading an image to a computer system in a search query; (b) the computer system using image recognition software to find images similar to the uploaded image in the search query; (c) the computer system displaying to the user the images that are similar to the uploaded image, wherein the display of images is presented to the user as a webpage, and wherein the webpage address is saved as a unique URL; (d) the user selecting one of the displayed images, thereby selecting an article of merchandise corresponding thereto; and (e) the user purchasing the article of merchandise.

Abstract: Disclosed herein are a method and apparatus that adaptively perform encoding and decoding based on image quality. An encoding apparatus may determine optimal Frames Per Second (FPS) for a video and may encode the video based on the determined FPS. Further, the encoding apparatus may provide improved temporal scalability. A decoding apparatus may select a frame to be displayed from among frames of a video depending on a required minimum satisfied user ratio. Through the selection of the frame, the decoding apparatus may provide improved temporal scalability.