Abstract: A method for detecting defects in products from images thereof and an electronic device applying the method inputs a defect image repair data set into an autoencoder to train the autoencoder, and generates a reconstructed image, calculates a reference error value between the sample image and the reconstructed image by a preset error function, and set a threshold value based on the reference error value. The electronic device inputs an image possibly revealing a defect into the autoencoder and generates the reconstructed image corresponding to the image to be detected, and uses the preset error function to calculate the reconstruction error between the image and the reconstructed image, thereby determining whether the image being analyzed does reveal defects. When the reconstruction error is greater than the threshold value, a determination is made that a defect is revealed.

Abstract: A side-wettable package with edge-recessed bond pads has a composite substrate, and the composite substrate is covered with a molding layer. An upper redistribution layer is formed on the molding layer, and the upper redistribution layer is covered with a solder mask and part of the upper redistribution is exposed to form at least one surface bond pad. Surfaces of each surface bond pad are formed with an anti-oxidation conductive layer, wherein at least one side surface of each surface bond pad is recessed relative to side surfaces of the molding layer. The present invention does not form the side-wettable structure by cutting the upper redistribution layer to prolong service life of cutting Wheels and structural stability of the package. The anti-oxidation conductive layer increases a contacting area between solder and each surface bond pad, thereby facilitating AOI instruments to determine soldering condition of the package and another component.

Abstract: A method for recognizing different object-categories within images based on texture classification of the different categories, which is implemented in an electronic device, includes extracting texture features from block images segmented from original images according to at least one Gabor filter; determining a grayscale level co-occurrence matrix of each block image according to the texture features; calculating texture feature statistics of each block image according to the grayscale level co-occurrence matrix; training and generating an object recognition model using the texture features and the texture feature statistics; and recognizing and classifying at least one object in original image according to the object recognition model.

Abstract: A projection lens includes a first and a second optical lens assembly. The first optical lens assembly is configured to transmit an image beam to the second optical lens assembly, which projects out the image beam from the projection lens. The second optical lens assembly includes a first and a second reflective element, and an optical member disposed between the first and the second reflective element and including a translucent region and a reflective region. The first reflective element is configured to reflect the image beam from the first optical lens assembly and transmit to the translucent region, which allows the image beam from the first reflective element to pass through and transmit to the second reflective element. The second reflective element is configured to reflect the image beam from the translucent region and transmit to the reflective region, which reflects the image beam from the second reflective element.

Abstract: A projection device includes a light source module, a display panel, a freeform-surface reflective mirror, and a projection lens. The light source module includes a light source, a first Fresnel lens element, and a second Fresnel lens element. The first Fresnel lens element and the second Fresnel lens element are parallel to each other and located between the light source and the display panel. The display panel is arranged between the light source module and the freeform-surface reflective mirror. The projection lens is configured to transmit an image beam out of the projection device, and a direction of an optical axis of the projection lens is different from a direction of a normal of the first Fresnel lens element.

Abstract: A charging module configured to charge a plurality of electric vehicles through a plurality of charging piles is provided. The charging module includes a charging prediction mode and a charging scheduling unit. The charging prediction mode is obtained according to a plurality of historical charging data, wherein each historical charging data includes an actual charging amount and at least one of a stay time and a charging time. The charging scheduling unit is configured to obtain a predicted electricity demand and a predicted stay period of each electric vehicle through the charging prediction model; and generate a charging schedule including: providing each electric vehicle with a basic charging amount; and determining a charging priority of the electric vehicles according to the predicted electricity demand and the predicted stay period.

Abstract: A p-GaN high-electron-mobility transistor, includes a substrate, a channel layer stacked on the substrate, a supply layer stacked on the channel layer, a first doped layer stacked on the supply layer, a second doped layer stacked on the first doped layer, and a third doped layer stacked on the second doped layer. A doping concentration of the first doped layer and the doping concentration of the third doped layer are lower than a doping concentration of the second doped layer. A gate is located on the third doped layer, and a source and a drain are electrically connected to the channel layer and the supply layer, respectively.

Abstract: A supporting assembly for an outdoor computing system is disclosed. The supporting assembly includes a holder having a base from which a peripheral wall extends and a foldable unit mechanically attached to the holder within the peripheral wall. The foldable unit has a first side, a second side connected to the first side and movable relative to the first side, and a third side connected to the first side and movable relative to the first side. The supporting assembly further includes a plurality of springs including a first spring and a second spring, the first spring being attached between the first side and the second side, the second spring being attached between the first side and the third side. The foldable unit is configured to change between an open configuration and a closed configuration, the foldable unit being maintained in the open configuration solely by the plurality of springs.

Abstract: An acoustic metasurface structure is configured to absorb sounds. The acoustic metasurface structure comprises a main body, an externally-connecting configuration and an inner configuration. The externally-connecting configuration and the inner configuration are respectively formed inside the main body. An externally-connecting tube of the externally-connecting configuration is in fluid communication with an external environment and an externally-connecting cavity of the externally-connecting configuration. An inner tube of the inner configuration is in fluid communication with the externally-connecting cavity and an inner cavity of the inner configuration. With the externally-connecting configuration and the inner configuration forming a series-type structure in the main body, the acoustic metasurface structure increases an acoustic impedance.

Abstract: The disclosure describes techniques for configuring wireless routers of a wireless mesh network with one or more secondary wireless access points (WAPs) such that client devices connected to the mesh network may remain online in the event that a primary WAP goes offline or otherwise becomes unavailable. For instance, a user of the wireless mesh network may specify a device, such as a mobile electronic device connected to a cellular network, to operate as a secondary WAP in the event that a primary WAP becomes unavailable. Thereafter, upon a wireless router of the mesh network detecting that the primary WAP is unavailable, the wireless router may perform a network scan to identify SSID(s) that are available within the environment. The wireless router may also instruct the other routers of the mesh network to perform a network scan.

Abstract: An attachable support module for attachment to an electronic equipment casing. The support module allows the electronic equipment casing to be raised from a ground surface to allow cables to be attached to the underside of the casing. The support module includes a case having an exterior plate and a parallel interior plate. A support member is rotatably mounted between the exterior plate and the interior plate of the case. The support member has a collapsed position within the case and an extended position extending from the case. A pivot arm engages the support member in the collapsed position.

Abstract: A method for neural network model encryption and decryption includes a first apparatus stores a neural network model and obtains hardware configuration information of the first apparatus, and obtains an encryption key accordingly; encrypts the neural network model by a predetermined encryption algorithm; a second apparatus obtains the encrypted neural network model from the first apparatus, transmits a decryption request to the first apparatus, obtains the hardware configuration information from the first apparatus, obtains a decryption key based on the hardware configuration information; and decrypts the encrypted neural network model by a predetermined decryption algorithm.

Abstract: A method for detecting and counting pedestrians in real-time for statistical purposes together with facial recognition of such pedestrians acquires video for analysis. Images showing pedestrians are extracted, such pedestrians being identified by a first detection model and pedestrian frames are outputted. A facial identification operation is executed based on the pedestrian frames and facial sub-frames are extracted. Removal of duplications of individual pedestrians in the images in the facial sub-frames is executed by a second detection model. Path of movement of detected pedestrians is tracked and labeled based on a specified algorithm when the faces of individual pedestrians are not recorded in a database. When the path of movement passes through a specified location, the face-imaged pedestrian is considered a target object, a total number of the target objects is counted. An apparatus applying the method is also disclosed.

Abstract: A semiconductor structure includes a substrate, a piezoelectric layer, and a stress structure. The substrate includes a first surface and a second surface, wherein a portion of the substrate proximal to the first surface defines a diaphragm. The piezoelectric layer is disposed over the first surface of the substrate and surrounds the diaphragm, wherein the piezoelectric layer includes a first portion and a second portion arranged along a periphery of the diaphragm from a top view. The stress structure includes a plurality of dielectric layers disposed over the piezoelectric layer and between the substrate and the piezoelectric layer, and a total thickness of a first portion of the stress structure overlapping the first portion of the piezoelectric layer is different from a total thickness of a second portion of the stress structure overlapping the second portion of the piezoelectric layer. A method for manufacturing a semiconductor structure is also provided.

Abstract: An image augmentation method applied to an electronic device is provided. The method includes constructing a variational learner and a discriminator based on a fully convolutional neural network. A target image is obtained by inputting a gas leakage image into the variational learner. A variational autoencoder model is obtained by training the variational learner based on a discrimination result of the discriminator on the target image. A reconstruction accuracy rate is calculated based on a test image, an augmented model is obtained by adjusting the variational autoencoder model based on the gas leakage image, in response that the reconstruction accuracy rate being less than a preset threshold; and an augmented image is obtained by inputting the image to be augmented into the augmented model.

Abstract: A method for detecting defects in product applied in a computer device inputs an image of a product under test to an automatic encoder to obtain a reconstructed image, and the image is segmented into N image blocks and the reconstructed image is segmented into N image blocks. The computer device associates each of the N testing blocks with one reconstructed blocks according to positions of the N testing blocks in the image and positions of the N reconstructed blocks in the reconstructed image. The computer device further calculates mean square errors between each of the N testing blocks and each of the N reconstructed blocks, and associates each mean square error with each of the N testing blocks, whether the product has defects being determined based on the mean square errors corresponding to each of the N testing blocks.

Abstract: A method for manufacturing a semiconductor structure is provided. The method may include several operations. A piezoelectric capacitor is formed over a substrate, wherein the piezoelectric capacitor includes a metal electrode. An intermediate layer is formed on the metal electrode, and is patterned using a first mask layer as a mask. A metal layer is formed on the intermediate layer, wherein the metal layer electrically connects to the metal electrode. The metal layer is patterned using a second mask layer, wherein the intermediate layer is within a coverage area of the metal layer from a top-view perspective after the patterning of the metal layer. A semiconductor structure thereof is also provided.

Abstract: An image augmentation method applied to an electronic device is provided. The method includes constructing a variational learner and a discriminator based on a fully convolutional neural network. A target image is obtained by inputting a gas leakage image into the variational learner. A variational autoencoder model is obtained by training the variational learner based on a discrimination result of the discriminator on the target image. A reconstruction accuracy rate is calculated based on a test image, an augmented model is obtained by adjusting the variational autoencoder model based on the gas leakage image, in response that the reconstruction accuracy rate being less than a preset threshold; and an augmented image is obtained by inputting the image to be augmented into the augmented model.

Abstract: A method for neural network model encryption and decryption includes a first apparatus stores a neural network model and obtains hardware configuration information of the first apparatus, and obtains an encryption key accordingly; encrypts the neural network model by a predetermined encryption algorithm; a second apparatus obtains the encrypted neural network model from the first apparatus, transmits a decryption request to the first apparatus, obtains the hardware configuration information from the first apparatus, obtains a decryption key based on the hardware configuration information; and decrypts the encrypted neural network model by a predetermined decryption algorithm.

Abstract: A method for augmenting defect sample data thereof includes acquiring a positive sample image and defect category information of a surface of a product; inputting the positive sample image and the defect category information to a generative adversarial network (GAN); and generating defect sample data corresponding to the defect category information. An apparatus and a non-transitory computer readable medium for augmenting defect sample data are also disclosed.