Abstract: The present disclosure provides a switch circuit and a control method thereof, a smart switch and a control system. The switch circuit includes a wireless communication module, a switch module coupled to a load, a switch-on power obtaining circuit, an energy storage circuit coupled with the wireless communication module and a switch-off power obtaining circuit. The load is coupled with a neutral wire. The switch-on power obtaining circuit is configured to output a first current to the energy storage circuit in response to the switch module being switched on. The switch-off power obtaining circuit is configured to output a second current to the energy storage circuit via the second power supply terminal in response to the switch module being switched off. The second current is less than the first current.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.

Abstract: The present invention discloses a spatial posture adjusting device for an optical axis of a microscopic monitoring system for a cellular fermentation tank. The adjusting device includes a base frame, where the base frame is fixedly provided with an up/down adjustment table; the up/down adjustment table is slidably connected to a load plate; the load plate is fixedly provided with a microscope adjustment mechanism and an illumination rotation adjustment mechanism in sequence; the illumination rotation adjustment mechanism includes a base; the base is fixedly connected to a first support frame; the first support frame is fixedly provided with an illuminator; the microscope adjustment mechanism includes a second support frame; the second support frame is fixedly provided with a clamping device; the clamping device is fixedly provided with a microscope device; the illumination rotation adjustment mechanism is fixedly connected with a mobile platform.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a progressive refinement network to refine alpha mattes generated utilizing a mask-guided matting neural network. In particular, the disclosed systems can use the matting neural network to process a digital image and a coarse guidance mask to generate alpha mattes at discrete neural network layers. In turn, the disclosed systems can use the progressive refinement network to combine alpha mattes and refine areas of uncertainty. For example, the progressive refinement network can combine a core alpha matte corresponding to more certain core regions of a first alpha matte and a boundary alpha matte corresponding to uncertain boundary regions of a second, higher resolution alpha matte. Based on the combination of the core alpha matte and the boundary alpha matte, the disclosed systems can generate a final alpha matte for use in image matting processes.

Abstract: Embodiments of the present disclosure disclose a model management apparatus, method and system, where the apparatus includes a model storage module and a model update module; the model storage module is configured to store at least one functional model; the model update module is connected to the model storage module, and is configured to obtain a target functional model to be updated from the model storage module according to a received update instruction, perform functional update on the target functional model to be updated based on a target model data set, and transmit an updated target functional model to the model storage module for storage; where the target functional model is called by a model application apparatus to cause the model application apparatus to implement a set function, and the model application apparatus and the model management apparatus are set up independently of each other.

Abstract: An optical computation system includes a light source configured to produce a pump beam, an optical modulator configured to modulate the pump beam based on the modulation mask to generate a modulated beam, a non-linear medium configured to convert a portion of the modulated beam to a second harmonic (SH) beam and to produce an output including the SH beam and an unconverted portion of the pump beam, and a dichroic mirror configured to receive the output of the non-linear medium and to decouple the SH beam and the unconverted portion of the pump beam, a detector configured to detect a first optical power of the unconverted portion of the pump beam and to detect a second optical power of the SH beam, and a controller configured to generate an updated modulation mask based on the first and second optical powers for transmission to the optical modulator.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a transformer-based encoder-decoder neural network architecture for generating alpha mattes for digital images. Specifically, the disclosed system utilizes a transformer encoder to generate patch-based encodings from a digital image and a trimap segmentation by generating patch encodings for image patches and comparing the patch encodings to areas of the digital image. Additionally, the disclosed system generates modified patch-based encodings utilizing a plurality of neural network layers. The disclosed system also generates an alpha matte for the digital image from the patch-based encodings utilizing a decoder that includes a plurality of upsampling layers connected to a plurality of neural network layers via skip connections.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media that generate a height map for a digital object portrayed in a digital image and further utilizes the height map to generate a shadow for the digital object. Indeed, in one or more embodiments, the disclosed systems generate (e.g., utilizing a neural network) a height map that indicates the pixels heights for pixels of a digital object portrayed in a digital image. The disclosed systems utilize the pixel heights, along with lighting information for the digital image, to determine how the pixels of the digital image project to create a shadow for the digital object. Further, in some implementations, the disclosed systems utilize the determined shadow projections to generate (e.g., utilizing another neural network) a soft shadow for the digital object. Accordingly, in some cases, the disclosed systems modify the digital image to include the shadow.

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for accurately and flexibly generating harmonized digital images utilizing an object-to-object harmonization neural network. For example, the disclosed systems implement, and learn parameters for, an object-to-object harmonization neural network to combine a style code from a reference object with features extracted from a target object. Indeed, the disclosed systems extract a style code from a reference object utilizing a style encoder neural network. In addition, the disclosed systems generate a harmonized target object by applying the style code of the reference object to a target object utilizing an object-to-object harmonization neural network.

Abstract: This disclosure describes one or more implementations of an alpha matting system that utilizes a deep learning model to generate alpha mattes for digital images utilizing an alpha-range classifier function. More specifically, in various implementations, the alpha matting system builds and utilizes an object mask neural network having a decoder that includes an alpha-range classifier to determine classification probabilities for pixels of a digital image with respect to multiple alpha-range classifications. In addition, the alpha matting system can utilize a refinement model to generate the alpha matte from the pixel classification probabilities with respect to the multiple alpha-range classifications.

Abstract: Disclosed is an environment forming apparatus suitable for biological cultivation in extraterrestrial space. The apparatus includes a shell and a biological cabin configured in an upper space of the shell. A light management system for importing light of biological growth from external world is configured in the upper space, a thermal management system for at least balancing a temperature of the upper space and a water supplying system and configured for providing water for creatures growth are both configured on the shell. The biological cabin and the like are set at the appropriate part of the shell, an environment which is relatively suitable for biological growth or cultivation can be created and simulated on an extraterrestrial star, a condition is provided for ecological cultivation of the extraterrestrial space, an ecosystem of the extraterrestrial space can be formed, and a smooth extraterrestrial space biological experiment process is guaranteed.

Abstract: A method of operating an electric power system, which may include: determining a charge state of a first battery unit and a charge state of a second battery unit; determining a difference between the charge state of the first battery unit and the charge state of the second battery unit; and determining whether to enable discharging simultaneously of both the first battery unit and the second battery unit, or to enable discharging of one of the first and second battery units, based on the difference between the charge state of the first battery unit and the charge state of the second battery unit. At least one of the first and second battery units may be a swappable battery unit. The disclosure further relates to an electric power system and to a computer executable code including instructions for operating an electric power system.

Abstract: An electric power system for an electric vehicle, including: first charging and discharging current paths connected to a first battery unit; second charging and discharging current paths connected to a second battery unit; third charging and discharging current paths for a connection with an electric control system of the vehicle; a first power switch between the first discharging current path and the third discharging current path; a second power switch between the second discharging current path and the third discharging current path; a controlling unit to set the first and second power switches based on states of the accumulators, at least one of the first and second battery units being swappable. A controller, a method, and a vehicle comprising the system are also disclosed.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that utilize a progressive refinement network to refine alpha mattes generated utilizing a mask-guided matting neural network. In particular, the disclosed systems can use the matting neural network to process a digital image and a coarse guidance mask to generate alpha mattes at discrete neural network layers. In turn, the disclosed systems can use the progressive refinement network to combine alpha mattes and refine areas of uncertainty. For example, the progressive refinement network can combine a core alpha matte corresponding to more certain core regions of a first alpha matte and a boundary alpha matte corresponding to uncertain boundary regions of a second, higher resolution alpha matte. Based on the combination of the core alpha matte and the boundary alpha matte, the disclosed systems can generate a final alpha matte for use in image matting processes.