The proposed Coordinate-Aware Feature Excitation (CAFE) module and Position-Aware Upsampling (Pos-Up) module both adhere to ...

⭐ Let's have a quick recap of our main idea. Full-screen viewing is recommended for better visual details. lawdis_show_quick_v5_small.mov We present LawDIS, a language-window-based controllable ...

Abstract: Since the number of superpixels is lower than that of pixels, superpixels can substantially speed up subsequent processing steps and have been widely used in synthetic aperture radar (SAR) ...

FLAMeS, a new convolutional neural network, enhances MS lesion segmentation accuracy using only T2-weighted FLAIR images, making it more applicable in clinical settings. The algorithm outperformed ...

Visual Attention Networks (VANs) leveraging Large Kernel Attention (LKA) have demonstrated remarkable performance in diverse computer vision tasks, often outperforming Vision Transformers (ViTs) in ...

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...

Abstract: A self-attention powered graph convolution network (GCN) is proposed for electrical resistance tomography (ERT) and ultrasonic transmission tomography (UTT) dual-modality tomography. It’s ...

1 International College, Chongqing University of Posts and Telecommunications, Chongqing, China 2 Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States To ...

If you find FDSSC useful in your research, please consider citing. Chicago/Turabian Style: Wang, Wenju; Dou, Shuguang; Jiang, Zhongmin; Sun, Liujie. 2018. "A Fast Dense Spectral–Spatial Convolution ...