Boe Technology Group Co., Ltd.

Chengdu Boe Optoelectronics Technology Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Sheng Guo

Jiandong Bao

Shuo Li

Haifeng Wang

Peng Zhou

Yue Liu

Yanjun Ma

Tian Wu

Weilin Lai

Xiaoguang Hu

Peng Hou

Dan Guo

Hongcheng Gao

Wenqiang Wang

Jiwei Wang

Chunyu Zhang

Qingqing Dang

Liji Cheng

Ao Huang

Kaipeng Deng

Lielin Jiang

Youchun Chen

A display substrate and a display device are disclosed, and the display substrate has a plurality of sub-pixels, and includes a base substrate, a driving circuit layer, a pixel definition layer and a light-emitting device layer, and a black matrix layer. Each sub-pixel includes a pixel driving circuit in the driving circuit layer and a light-emitting device in the light-emitting device layer. The black matrix layer includes a plurality of first light-transmitting openings respectively exposing the light-emitting devices of the plurality of sub-pixels in a direction perpendicular to a surface of the base substrate. The pixel definition layer includes a plurality of sub-pixel openings, at least part of the plurality of sub-pixel openings are in one-to-one correspondence with and at least partially overlapped with the plurality of first light-transmitting openings, and at least one of the plurality of first light-transmitting openings has an arc-shaped edge.

Display substrate and display device

Embodiments of the present disclosure provide a method and apparatus of training a model, an electronic device, a storage medium and a development system, which relate to a field of deep learning. The method may include calling a training preparation component to set at least a loss function and an optimization function for training the model, in response to determining that a training preparation instruction is received. The method further includes calling a training component to set a first data reading component, in response to determining that a training instruction is received. The first data reading component is configured to load a training data set for training the model. In addition, the method may further include training the model based on the training data set from the first data reading component, by using the loss function and the optimization function through the training component.

Model development tool to train, evaluate and predict with deep learning by selecting functions

Embodiments of the application provide a display panel, a display screen and a display device. The display panel includes a backplane, a color filter layer, and a black matrix between the backplane and the color filter layer. The backplane includes a base substrate, the color filter layer includes a plurality of sub-pixel color filters, and the plurality of sub-pixel color filters are arranged along a plane of the color filter layer and spliced together to form the color filter layer.

Display panel, display screen and display device having larger viewing angle

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Beijing, China

Sheng Guo