Abstract: A display device includes a double-sided display module. The double-sided display module includes first and second display modules arranged back to back and connectors. Each connector includes at least one first connection hole and at least one second connection hole. The first display module includes first connection portions. The second display module includes second connection portions; and positions of the connectors, the first connection portions and the second connection portions are in one-to-one correspondence; the first display module and the second display module are fixedly connected to the connectors through the first connection portions and the second connection portions; and each first connection portion is connected to a connector through one of a first connection hole and a second connection hole of the connector, and each second connection portion is connected to the connector through another of a first connection hole and a second connection hole of the connector.

Abstract: A display assembly includes a display device, a first clamping plate and a second clamping plate. The display apparatus has at least one display area, and the first clamping plate and the second clamping plate are disposed on two opposite sides of the display device in a thickness direction thereof. At least one of the first clamping plate and the second clamping plate is located on at least one light-emitting side of the display device, and in a clamping plate located on a light-emitting side of the display device, at least a partial region of a portion covering an active area of the display device is in a transparent state. The display device includes a double-sided display module including a first display module and a second display module that are arranged back to back and an encapsulation housing configured to fix the first display module and the second display module.

Abstract: A tandem photovoltaic device includes: a tunnel junction between an upper cell unit and a lower cell unit. The lower cell unit is a crystalline silicon cell. The tunnel junction includes: a carrier transport layer, a crystalline silicon layer, and an intermediate layer located between the carrier transport layer and the crystalline silicon layer. The carrier transport layer is a metal oxide layer. The intermediate layer includes a tunneling layer. The crystalline silicon layer has a doping concentration greater than or equal to 1017 cm?3. The carrier transport layer is in direct contact with a shadow surface of the upper cell unit. If the crystalline silicon layer is a p-type crystalline silicon layer, a first energy level is close to a second energy level. If the crystalline silicon layer is an n-type crystalline silicon layer, a third energy level is close to a fourth energy level.

Abstract: The present disclosure relates to the field of photovoltaic technologies. Disclosed are a solar cell and a photovoltaic module. The solar cell includes: an absorption layer; and an energy selective contact layer located on a surface of the absorption layer, the energy selective contact layer having selectivity for electron energy or hole energy, and the material of the energy selective contact layer including a low-dimensional perovskite material. According to the solar cell and the photovoltaic module provided by the present disclosure, a photovoltaic module can be manufactured.

Abstract: The present disclosure provides a battery compartment and a handle for use in a transportation vehicle. The battery compartment includes: a battery mount having at least two battery mounting grooves spaced apart from each other; a connection electrode on the battery mount and between adjacent battery mounting grooves; a battery compartment cover detachably connected to the connection electrode; and a pushing-out assembly on the connection electrode, wherein the pushing-out assembly is configured to provide a force for moving the battery compartment cover away from the connection electrode.

Abstract: Disclosed is an electronic apparatus, including: a display device, a base, a detachable connector, an auxiliary display module, and a placement portion for placing the auxiliary display module, the display device being disposed on the base through the detachable connector.

Abstract: The present disclosure relates to a gait recognition method based on deep learning, which comprises recognizing an identity of a person in a video according to the gait thereof through dual-channel convolutional neural networks sharing weights by means of the strong learning capability of the deep learning convolutional neural network. Said method is quite robust to gait changes across a large view, which can effectively solve the problem of low precision in cross-view gait recognition existing with the prior art gait recognition technology. Said method can be widely used in scenarios having video monitors, such as security monitoring in airports and supermarkets, person recognition, criminal detection, etc.

Abstract: A human-shape image segmentation method comprising: extracting multi-scale context information for all first pixel points for training a human-shape image; sending image blocks of all scales of all the first pixel points into a same convolution neural network to form a multi-channel convolutional neural network group, wherein each channel corresponds to image blocks of one scale; training the neural network group using a back propagation algorithm to obtain human-shape image segmentation training model data; extracting multi-scale context information for all second pixels points for testing the human-shape image; sending image blocks of different scales of each of the second pixel points into a neural network channel corresponding to the human-shape image segmentation training model, wherein if said first probability is larger than said second probability, the second pixel points belong to the human-shape region, otherwise, the second pixel points are outside of the human-shape region.

Abstract: The present disclosure relates to a gait recognition method based on deep learning, which comprises recognizing an identity of a person in a video according to the gait thereof through dual-channel convolutional neural networks sharing weights by means of the strong learning capability of the deep learning convolutional neural network. Said method is quite robust to gait changes across a large view, which can effectively solve the problem of low precision in cross-view gait recognition existing with the prior art gait recognition technology. Said method can be widely used in scenarios having video monitors, such as security monitoring in airports and supermarkets, person recognition, criminal detection, etc.

Abstract: A human-shape image segmentation method comprising: extracting multi-scale context information for all first pixel points for training a human-shape image; sending image blocks of all scales of all the first pixel points into a same convolution neural network to form a multi-channel convolutional neural network group, wherein each channel corresponds to image blocks of one scale; training the neural network group using a back propagation algorithm to obtain human-shape image segmentation training model data; extracting multi-scale context information for all second pixels points for testing the human-shape image; sending image blocks of different scales of each of the second pixel points into a neural network channel corresponding to the human-shape image segmentation training model, wherein if said first probability is larger than said second probability, the second pixel points belong to the human-shape region, otherwise, the second pixel points are outside of the human-shape region.