Abstract: A memory device, includes a memory array for storing a plurality of vector data each of which has an MSB vector and a LSB vector. The memory array includes a plurality of memory units each of which has a first bit and a second bit. The first bit is used to store the MSB vector of each vector data, the second bit is used to store the LSB vector of each vector data. A bit line corresponding to each vector data executes one time of bit-line-setup, and reads the MSB vector and the LSB vector of each vector data according to the bit line. The threshold voltage distribution of each memory unit is divided into N states, where N is a positive integer and N is less than 2 to the power of 2, and the effective bit number stored by each memory unit is less than 2.

Abstract: A method of forming a semiconductor structure is provided, and includes trimming a first substrate to form a recess on a sidewall of the first substrate. A conductive structure is formed in the first substrate. The method includes bonding the first substrate to a carrier. The method includes thinning down the first substrate. The method also includes forming a dielectric material in the recess and over a top surface of the thinned first substrate. The method further includes performing a planarization process to remove the dielectric material and expose the conductive structure over the top surface. In addition, the method includes removing the carrier from the first substrate.

Abstract: A bonding structure that may be used to form 3D-IC devices is formed using first oblong bonding pads on a first substrate and second oblong bonding pads one a second substrate. The first and second oblong bonding pads are laid crosswise, and the bond is formed. Viewed in a first cross-section, the first bonding pad is wider than the second bonding pad. Viewed in a second cross-section at a right angle to the first, the second bonding pad is wider than the first bonding pad. Making the bonding pads oblong and angling them relative to one another reduces variations in bonding area due to shifts in alignment between the first substrate and the second substrate. The oblong shape in a suitable orientation may also be used to reduce capacitive coupling between one of the bonding pads and nearby wires.

Abstract: A waste collection apparatus for collecting waste in water is provided. The waste collection apparatus includes a floating device and a waste collection device coupled to the floating device. The floating device includes a plurality of floating units. The waste collection device is coupled to the floating device. Each of the floating units includes a base and a pillar connected to the base, and the density of the base is greater than the density of the pillar.

Abstract: A waste collection apparatus for collecting waste in water is provided. The waste collection apparatus includes a floating device and a waste collection device coupled to the floating device. The waste collection device includes a fluid ejection element, and the flow out of the fluid ejection element flows toward a space where waste is collected.

Abstract: The present disclosure is directed to a wafer drying system and method that detects airborne molecular contaminants in a drying gas as a feedback parameter for a single wafer or multi-wafer drying process. For example, the system comprises a wafer drying station configured to dispense a drying gas over one or more wafers to dry the one or more wafers, a valve configured to divert the drying gas to a first portion and a second portion, and an exhaust line configured to exhaust the first portion of the drying gas. The system further comprises a detector configured to receive the second portion of the drying gas and to determine a real time property of the second portion of the drying gas, and a control unit configured to control a feedback operation of the wafer drying station based on the real time property of the second portion of the drying gas.

Abstract: Various embodiments of the present disclosure are directed towards an image sensor including first chip and a second chip. The first chip includes a first substrate, a plurality of photodetectors disposed in the first substrate, a first interconnect structure disposed on a front side of the first substrate, and a first bond structure disposed on the first interconnect structure. The second chip underlies the first chip. The second chip includes a second substrate, a plurality of semiconductor devices disposed on the second substrate, a second interconnect structure disposed on a front side of the second substrate, and a second bond structure disposed on the second interconnect structure. A first bonding interface is disposed between the second bond structure and the first bond structure. The second interconnect structure is electrically coupled to the first interconnect structure by way of the first and second bond structures.

Abstract: In an embodiment, a method includes: immersing a wafer in a bath within a cleaning chamber; removing the wafer out of the bath through a solvent and into a gas within the cleaning chamber; determining a parameter value from the gas; and performing remediation within the cleaning chamber in response to determining that the parameter value is beyond a threshold value.

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.

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 method for detecting defects in products revealed by images of the products inputs images of the flaw-free products into an autoencoder for model training to obtain reconstructed images. The images are further processed to obtain target images. A group of testing errors are obtained by comparing the reconstructed images and the target images. An error threshold is selected from the group of the testing errors according to a specified rule. A to-be-analyzed image is inputted for obtaining a candidate be-analyzed reconstructed image, a candidate be-analyzed target image, and a potential be-analyzed error between the candidate be-analyzed reconstructed image and the candidate be-analyzed target image. A result of the to-be-analyzed image confirms defects existing or defects not existing according to the potential be-analyzed error and the error threshold. A defect detection apparatus, an electronic device, and a non-transitory computer-readable storage medium applying the method are also disclosed.

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 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 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: Disclosures of the present invention describe a halide semiconductor memristor that is suitable for being as an artificial synapse. The halide semiconductor memristor comprises a first electrode layer, an active layer and a second electrode layer, wherein the active layer comprises a first oxide semiconductor film formed on the first electrode layer, a halide semiconductor film formed on the first oxide semiconductor film, and a second oxide semiconductor film formed on the halide semiconductor film Moreover, a variety of experimental data have proved that, this halide semiconductor memristor is indeed suitable for being adopted as a plurality of artificial synapses that are used in manufacture of a neuromorphic device, and exhibits many advantages, including: capable of being driven by a low operation voltage, having a multi-stage adjustable resistance state, and a wide dynamic range of the switching resistance states.

Abstract: A method of determining a parameter of a pattern transfer process and device manufacturing methods are disclosed. In one arrangement, a method includes obtaining a detected representation of radiation redirected by a structure. The structure is a structure formed by applying a pattern processing to a pattern transferred to an earlier formed structure by a pattern transfer process. The pattern processing is such as to remove one or more selected regions in a horizontal plane of the earlier formed structure to form a pattern in the horizontal plane. The pattern is defined by a unit cell that is mirror symmetric with respect to an axis of mirror symmetry. An asymmetry in the detected representation is determined. The determined asymmetry in the detected representation is used to determine a parameter of the pattern transfer process.