… fusion network (DFFN) to classify HSIs. Different from the previous networks used in HSI
classification… can ease the training of a deep network and benefit from increasing depth. With the …

… the network (MS-FC-DenseNet) in each scale requires several dense block (see Fig. 3), such
a fusion strategy will make the whole multiscale fusion network … a novel fusion strategy to …

… To solve this problem, a multi-branch fusion network is proposed in this work. As shown in
Fig. 3, the proposed CNN adds two branches into the middle of the original CNN in Section 2.2…

… hyperspectral image classification. To achieve this, we propose a two-stream spectral feature
fusion … Then, the two parallel classifiers are integrated adaptively via a decision fusion. At …

… for classification. In this paper, we propose a novel fully dense multiscale fusion network (…
hierarchical features from all the convolutional layers for HSI classification. In the proposed …

… This paper proposes a fusion network of convolution and Transformer for HSI classification,
… Experimental results demonstrate that the proposed network has superior classification …

… propose a feature fusion hypergraph neural network (F2HNN) for HSI classification. F2HNN
… hypergraph convolutional neural network for learning. In addition, we propose three feature …

… To further analyze the advantage of multiscale feature fusion strategy, we show the
classification results on each class by DS 2 F 2 at three pooling scales, as well as by DMS …

… To handle these issues, in this article, a novel adaptive spectral-spatial feature fusion
network (AS 2 F 2 N) is proposed for HSIC. AS 2 F 2 N contains two sub-networks that extract …

… and multiscale convolutional fusion network for hyperspectral image classification,” IEEE …
, “Hyperspectral image classification based on multibranch attention transformer networks,” …