Abstract: A computer-implemented method includes obtaining a trained convolutional neural network comprising one or more convolutional layers, each of the one or more convolutional layers comprising a plurality of filters with known filter parameters; pre-computing a reusable factor for each of the one or more convolutional layers based on the known filter parameters of the trained convolutional neural network; receiving input data to the trained convolutional neural network; computing an output of the each of the one or more convolutional layers using a Winograd convolutional operator based on the pre-computed reusable factor and the input data; and determining output data of the trained convolutional network based on the output of the each of the one or more convolutional layers.

Abstract: A computer-implemented method includes obtaining a trained convolutional neural network comprising one or more convolutional layers, each of the one or more convolutional layers comprising a plurality of filters with known filter parameters; pre-computing a reusable factor for each of the one or more convolutional layers based on the known filter parameters of the trained convolutional neural network; receiving input data to the trained convolutional neural network; computing an output of the each of the one or more convolutional layers using a Winograd convolutional operator based on the pre-computed reusable factor and the input data; and determining output data of the trained convolutional network based on the output of the each of the one or more convolutional layers.

Abstract: N vehicle accident images are obtained, where N is a natural number greater than or equal to 2. N feature vectors are obtained by inputting the vehicle accident images into a trained convolutional neural network, where the N feature vectors respectively correspond to the vehicle accident images. A distance is calculated between any two feature vectors of the N feature vectors. A determination is made that two vehicle accident images of the N vehicle accident images corresponding to the distance are abnormal when the distance is greater than a first predetermined threshold.

Abstract: Provided are a positive electrode plate and a lithium ion battery. The positive electrode plate includes a positive electrode current collector and a positive electrode active material layer. The positive electrode active material layer includes a first sub-layer as the outermost sub-layer of the positive active material layer, and a second sub-layer disposed between the positive electrode current collector and the first sub-layer. The first sub-layer includes a first positive electrode active material, the second sub-layer includes a second positive electrode active material. The first positive electrode active material is one or more of a ternary positive electrode material having a monocrystalline or quasi-monocrystalline structure, and a coating-modified material thereof. The present disclosure can improve energy density of the lithium ion battery and reduce gas production of the lithium ion battery, so that the lithium ion battery has high energy density and good storage performance at the same time.

Abstract: N vehicle accident images are obtained, where N is a natural number greater than or equal to 2. N feature vectors are obtained by inputting the vehicle accident images into a trained convolutional neural network, where the N feature vectors respectively correspond to the vehicle accident images. A distance is calculated between any two feature vectors of the N feature vectors. A determination is made that two vehicle accident images of the N vehicle accident images corresponding to the distance are abnormal when the distance is greater than a first predetermined threshold.

Abstract: The disclosure provides a modified positive electrode active material, a preparation method thereof, and an electrochemical energy storage device. The modified positive electrode active material comprises positive electrode active material substrate; first oxide layer, coated on the surface of the positive electrode active material substrate and selected from one or more of oxides of element M being selected from the group of one or more of Li, Al, Zr, Mg, Ti, Y, Si, Ca, Cr, Fe, Zn, Nb, Sn, Ba, and Cd; and second oxide layer having a continuous layered structure, coated on the surface of the first oxide layer and selected from one or more of oxides of element M? being selected from one or more of Li, B, P, As, Pb, V, Mo, and Sn. High temperature storage performance and cycling performance of electrochemical energy storage device are improved by the modified positive electrode active material.

Abstract: The present document discloses a photographing method, device and terminal. The photographing method includes: in a pre-photographing state, receiving a request of a user for marking a specific photographing area of a photographing preview interface, generating mark information according to the request and displaying the mark information at a corresponding position on the photographing preview interface; in a formal photographing state, displaying image information obtained by a camera and the mark information on the photographing preview interface at the same time; and executing a photographing operation after receiving a photographing instruction.

Abstract: The present document discloses a photographing method, device and terminal. The photographing method includes: in a pre-photographing state, receiving a request of a user for marking a specific photographing area of a photographing preview interface, generating mark information according to the request and displaying the mark information at a corresponding position on the photographing preview interface; in a formal photographing state, displaying image information obtained by a camera and the mark information on the photographing preview interface at the same time; and executing a photographing operation after receiving a photographing instruction.