Dalian University

North China Electric Power University

State Grid Liaoning Electric Power Supply Co., Ltd.

Qiang Zhang

XiaoPeng Wei

Xu Zhang

Li Liu

Xin Wu

Jun Lu

Bo Hu

Chang Su

Rongrong Chen

Yuandi Shi

Ren Qiang

Yutong Wang

Ao Yu

Qiang Fang

Jichao Dong

Yilin Liu

Yurui Wang

Luning Jiang

Wanli Cui

Jiuliang Liu

Jun Tan

Zongle Ma

Chunhua Lin

Luyao Wang

Qiguo Zhang

Shengjie Zhou

Gangjun Gong

Meinan Lin

Jiaxuan Yang

Linan Feng

The present disclosure discloses a method for watermarking depth image based on mixed frequency-domain channel attention, relating to the field of artificial neural networks and digital image watermarking; the method includes: step 1: a watermark information processor generating a watermark information feature map; step 2: an encoder generating a watermarked image from a carrier image and a watermark information feature map; step 3: a noise layer taking the watermarked image as an input, and generating a noise image through simulated differentiable noise; step 4: a decoder down-sampling the noise image to recover watermark information; step 5: a countermeasure discriminator classifying the carrier image and the watermarked image such that the encoder generates a watermarked image with a high quality. The present disclosure combines the end-to-end depth watermark model with frequency-domain channel attention to expand an application range of the depth neural network in the field of image watermark.

Method for watermarking depth image based on mixed frequency-domain channel attention

The present disclosure discloses a method for encrypting a visually secure image based on adaptive block compressed sensing and non-negative matrix decomposition. Firstly, the Tetrolet transform is performed on the plain image, then the sparsity degree is optimized on the sparsity matrix and the matrix scrambling is performed, such that the sparsity degree in each block region of the image matrix is equalized. Then according to the image information, the sampling number of the block region is calculated, the measurement matrix is constructed and optimized, and the image is compressed by using the optimized measurement matrix. The compressed image is then scrambled and diffused to complete the encryption process. Finally, the image information is embedded into the carrier image through non-negative matrix decomposition to obtain a visually safe ciphertext image. The decryption process is the inverse of the encryption process.

Method for encrypting visually secure image

Provided are a method for tracking carbon flow of a power system, a device and a medium. The method includes: acquiring related data of carbon flow tracking, where the related data include an injected active power sum column matrix of generator sets of all substations to be tracked, an injected carbon flow rate sum column matrix of generator sets of all substations to be tracked, an output power distribution matrix of a branch formed between substations to be tracked, and a power flow proportion distribution matrix of the branch formed between substations to be tracked; acquiring a carbon potential matrix Eof each substation to be tracked; and acquiring a carbon flow rate of each substation to be tracked, a carbon flow rate of the branch, and a carbon flow rate of an output load on the basis of the carbon potential matrix of each substation to be tracked.

Method for tracking carbon flow of power system, device and medium

Growing community of inventors

Dalian, China

Qiang Zhang