Abstract: Examples in the present disclosure relate to prompt-driven, conversation-specific image generation. A first user device of a first user of an interaction application transmits an image generation request. The interaction application enables the first user to interact with at least a second user. An image is automatically generated based on a prompt included in the image generation request, and the image is presented at the first user device. In response to receiving user input to select the image, the image is stored as a conversation-specific image in association with a first user profile of the first user and a second user profile of the second user. The conversation-specific image is presented at both the first user device of the first user and a second user device of the second user, together with conversation data associated with a conversation between the first user and the second user.

Abstract: A messaging system performs neural network hair rendering for images provided by users of the messaging system. A method of neural network hair rendering includes processing a three-dimensional (3D) model of fake hair and a first real hair image depicting a first person to generate a fake hair structure, and encoding, using a fake hair encoder neural subnetwork, the fake hair structure to generate a coded fake hair structure. The method further includes processing, using a cross-domain structure embedding neural subnetwork, the coded fake hair structure to generate a fake and real hair structure, and encoding, using an appearance encoder neural subnetwork, a second real hair image depicting a second person having a second head to generate an appearance map. The method further includes processing, using a real appearance renderer neural subnetwork, the appearance map and the fake and real hair structure to generate a synthesized real image.

Abstract: Examples described herein relate to automatic image generation. A plurality of inputs is accessed. The inputs include first input data and second input data. The first input data includes a text prompt describing a desired image and the second input data is indicative of one or more structural features of the desired image. One or more intermediate outputs are generated via a first generative machine learning model that uses the plurality of inputs as first control signals. An output image is generated via a second generative machine learning model that uses at least a subset of the plurality of inputs and at least a subset of the one or more intermediate outputs as second control signals. The output image is presented at a user device of a user.

Abstract: The present disclosure provides a back plate for use in a display apparatus, wherein the back plate includes: a bottom wall; a through hole in the bottom wall, wherein the through hole is provided with a hole wall protruding towards a side of the bottom wall, and the hole wall and the bottom wall are connected together and have a one-piece structure, wherein materials of the bottom wall and the hole wall each include an aluminum alloy material. The present disclosure further provides a manufacturing method of the back plate, a backlight module and a display apparatus.

Abstract: A vision transformer network having extremely low latency and usable on mobile devices, such as smart eyewear devices and other augmented reality (AR) and virtual reality (VR) devices. The transformer network processes an input image, and the network includes a convolution stem configured to patch embed the image. A first stack of stages including at least two stages of 4-Dimension (4D) metablocks (MBs) (MB4D) follow the convolution stem. A second stack of stages including at least two stages of 3-Dimension MBs (MB3D) follow the MB4D stages. Each of the MB4D stages and each of the MB3D stages include different layer configurations, and each of the MB4D stages and each of the MB3D stages include a token mixer. The MB3D stages each additionally include a multi-head self attention (MHSA) processing block.

Abstract: A patient state monitoring system and method, applied to a patient state monitoring system comprising a monitoring device and a monitoring module communicationally connected to the monitoring device, the monitoring module being worn on the patient's body, the patient state monitoring system also comprising a processor. The method includes: a processor obtains parameters, and sets the operating mode of a monitoring module according to the obtained parameters, wherein the operating mode of the monitoring module includes a continuous monitoring module and an intermittent monitoring mode. By use of the patient state monitoring system and method, during the monitoring of a patient, strict monitoring of the user's physical condition can be satisfied and the processing of redundant data can be reduced, thereby improving monitoring efficiency and quality.

Abstract: System and methods for compressing image-to-image models. Generative Adversarial Networks (GANs) have achieved success in generating high-fidelity images. An image compression system and method adds a novel variant to class-dependent parameters (CLADE), referred to as CLADE-Avg, which recovers the image quality without introducing extra computational cost. An extra layer of average smoothing is performed between the parameter and normalization layers. Compared to CLADE, this image compression system and method smooths abrupt boundaries, and introduces more possible values for the scaling and shift. In addition, the kernel size for the average smoothing can be selected as a hyperparameter, such as a 3×3 kernel size. This method does not introduce extra multiplications but only addition, and thus does not introduce much computational overhead, as the division can be absorbed into the parameters after training.

Abstract: Examples disclosed herein describe techniques related to automated image generation in an interaction system. An image generation request is received from a first user device associated with a first user of an interaction system. The image generation request comprises a text prompt. Responsive to receiving the image generation request, an image is automatically generated by an automated text-to-image generator, based on the text prompt. The image is caused to be presented on the first user device. An indication of user input to select the image is received from the user device. Responsive to receiving the indication of the user input to select the image, the image is associated with the first user within the interaction system, and a second user of the interaction system is enabled to be presented with the image.

Abstract: Backlight module and display device are disclosed. The backlight module includes a light source structure and a light guide plate, which includes a body structure and a wedge-shaped structure disposed on the body structure and located at a side adjacent to the light source structure. The body structure includes a light incident surface of body structure. The wedge-shaped structure includes a bottom surface, a wedge surface and a light incident surface of wedge-shaped structure. The light source structure includes a light source, light emitted by which enters the light guide plate through the light incident surface of body structure and the light incident surface of wedge-shaped structure. In a direction perpendicular to the bottom surface, a ratio of thickness of the body structure to thickness of light-exiting surface of the light source is less than or equal to 88%.

Abstract: The embodiments of the present disclosure disclose an evaluation apparatus and a method for seal integrity of a wellbore in a full life cycle. The apparatus may include an oil pipe temperature and pressure simulation assembly, an oil casing annular temperature and pressure simulation assembly, a formation confining pressure simulation assembly, a casing-cement sheath-formation combination preparation assembly, a blowby characteristic detection assembly, and a monitoring system. The present disclosure may crustal stress quickly complete scanning of cement slurry system and maintenance and preparation of casing-cement sheath-formation combination, intelligent monitor blowby pressure of cement sheath in real time, test the critical blowby pressure curve of cement sheath of oil and gas wells under various production conditions throughout the life cycle for evaluating the seal integrity of wellbore, and provide technical support for the formulation of wellbore safeguard measures.

Abstract: The present disclosure provides a connection structure, a display panel, a manufacturing method, a detection circuitry and a display device. The connection structure includes a connection unit. The connection unit includes a first connection member, a second connection member, and a binding member. The first connection member includes a plurality of first connectors, the second connection member includes a plurality of second connectors, the binding member includes a plurality of binding pins, the connection unit includes a plurality of metal layers and a plurality of insulation layers, the second connector includes a second connection line, the second connection line includes at least two second connection line portions electrically coupled to each other, and at least two insulation layers in the connection unit are arranged on a side of the at least two metal layers away from the base substrate.

Abstract: An electronic device is provided. The device includes a metal frame. The metal frame includes a first side and the first side includes three metal segments separated by two first gaps. The three metal segments include a first metal segment and the first metal segment is used to realize a first antenna. An operating frequency band of the first antenna at least includes 5 GHz to enable the electronic device to support a fifth-generation mobile communication network.

Abstract: A display module, a preparing method therefor and a display device are provided. The display module includes a back plate and a mold frame, the back plate includes a base plate, the base plate includes an edge region, the mold frame is disposed on the edge region, the edge region is provided with a rough structure region, the rough structure region includes multiple rough structures, an orthographic projection of at least part of the rough structures on the base plate overlaps with an orthographic projection of the mold frame on the base plate, and a material of the mold frame fills at least part of space of the rough structures.

Abstract: A packaging member and a manufacturing method therefor, a backlight source assembly, and a display apparatus. The packaging member comprises a cup-shaped support (1), a light-emitting chip (2), and a packaging glue (3) mixed with a photoluminescent material (4); the light-emitting chip (2) is fixed at the bottom of the support (1) and emits light towards an opening of the support (1); the packaging glue (3) covers the light-emitting chip (2); and the packaging member comprises a light scattering structure, and the light scattering structure is configured to scatter light.

Abstract: Described is a system for improving machine learning models by accessing a first latent diffusion machine learning model, accessing a second latent diffusion machine learning model that was derived from the first latent diffusion machine learning model, the second latent diffusion machine learning model trained to perform a second number of denoising steps, generating noise data, processing the noise data via the first latent diffusion machine learning model to generate one or more first latent features, processing the noise data via the second latent diffusion machine learning model to generate one or more second latent features, and inputting the one or more first latent features and the one or more second latent features into a loss function. The system then modifies a parameter of the second latent diffusion machine learning model based on the output of the loss function.

Abstract: Described is a system for improving machine learning models. In some cases, the system improves such models by identifying a performance characteristic for machine learning model blocks in an iterative denoising process of a machine learning model, connecting a prior machine learning model block with a subsequent machine learning model block of the machine learning model blocks within the machine learning model based on the identified performance characteristic, identifying a prompt of a user, the prompt indicative of an intent of the user for generative images, and analyzing data corresponding to the prompt using the machine learning model to generate one or more images, the machine learning model trained to generate images based on data corresponding to prompts.

Abstract: Described is a system for improving machine learning models by accessing a first latent diffusion machine learning model, the first latent diffusion machine learning model trained to perform a first number of denoising steps, accessing a second latent diffusion machine learning model that was derived from the first latent diffusion machine learning model, the second latent diffusion machine learning model trained to perform a second number of denoising steps, generating noise data, processing the noise data via the first latent diffusion machine learning model to generate one or more first images, processing the noise data via the second latent diffusion machine learning model to generate one or more second images, and modify a parameter of the second latent diffusion machine learning model based on a comparison of the one or more first images with the one or more second images.

Abstract: Described is a system for improving machine learning models. In some cases, the system improves such models by identifying an autoencoder for a latent diffusion machine learning model, the latent diffusion machine learning model is trained to receive text as input and output an image based on the received text. The system identifies a number of channels in a decoder of the autoencoder, the decoder being configured to receive latent features as input and output images. The system further identifies a performance characteristic of the decoder and changes the node topology of the decoder based on the performance characteristic to generate an updated decoder. The system retrains the latent diffusion machine learning model using the updated decoder by inputting latent features to the updated decoder, receiving an outputted image from the updated decoder, and updating one or more weights of the decoder based on an assessment of the outputted image.

Abstract: System and methods for compressing image-to-image models. Generative Adversarial Networks (GANs) have achieved success in generating high-fidelity images. An image compression system and method adds a novel variant to class-dependent parameters (CLADE), referred to as CLADE-Avg, which recovers the image quality without introducing extra computational cost. An extra layer of average smoothing is performed between the parameter and normalization layers. Compared to CLADE, this image compression system and method smooths abrupt boundaries, and introduces more possible values for the scaling and shift. In addition, the kernel size for the average smoothing can be selected as a hyperparameter, such as a 3×3 kernel size. This method does not introduce extra multiplications but only addition, and thus does not introduce much computational overhead, as the division can be absorbed into the parameters after training.

Abstract: A patient state monitoring system and a method for monitoring patient state are disclosed. The patient state monitoring system includes a monitoring device and a monitoring module communicationally connected to the monitoring device, the monitoring module being worn on the patient's body. The patient state monitoring system also includes a processor that obtains parameters, and sets the operating mode of a monitoring module according to the obtained parameters, where the operating mode of the monitoring module comprises a continuous monitoring module and an intermittent monitoring mode. By use of the patient state monitoring system and method, during the monitoring of a patient, strict monitoring of the user's physical condition can be satisfied and the processing of redundant data can be reduced, thereby improving monitoring efficiency and quality.