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DCNN: Dual Cross-current Neural Networks Realized Using An Interactive Deep Learning Discriminator for Fine-grained Objects

Autor: Fu, Da, Rong, Mingfei, Kim, Eun-Hu, Huang, Hao, Pedrycz, Witold

Accurate classification of fine-grained images remains a challenge in backbones based on convolutional operations or self-attention mechanisms. This study proposes novel dual-current neural networks (DCNN), which combine the advantages of convolution

Externí odkaz: http://arxiv.org/abs/2405.04093

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Superior ferroelectricity and nonlinear optical response in a hybrid germanium iodide hexagonal perovskite

Autor: Ding, Kun, Ye, Haoshen, Su, Changyuan, Xiong, Yu-An, Du, Guowei, You, Yu-Meng, Zhang, Zhi-Xu, Dong, Shuai, Zhang, Yi, Fu, Da-Wei

Publikováno v: Nature Communications 14, 2863-2023 (2023)

Abundant chemical diversity and structural tunability make organic-inorganic hybrid perovskites (OIHPs) a rich ore for ferroelectrics. However, compared with their inorganic counterparts such as BaTiO$_3$, their ferroelectric key properties, includin

Externí odkaz: http://arxiv.org/abs/2305.11721

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