Abstract: Accurate semantic segmentation of remote sensing data plays a crucial role in the success of geoscience research and applications. Recently, multimodal fusion-based segmentation models have ...

Abstract: There are still various challenges in remote sensing semantic segmentation due to objects diversity and complexity. Transformer-based models have significant advantages in capturing global ...

Abstract: To better characterize the differences in category features in Facial Expression Recognition (FER) tasks, and improve inter-class separability and intra-class compactness, we propose a ...

Abstract: Multilabel feature selection solves the dimension distress of high-dimensional multilabel data by selecting the optimal subset of features. Noisy and incomplete labels of raw multilabel data ...

Abstract: Unmanned aerial vehicle (UAV) image target detection holds significant value for a wide range of applications in modern society. However, due to the variable flight altitude of UAV, the ...

Abstract: Oriented object detection in aerial images has made significant advancements propelled by well-developed detection frameworks and diverse representation approaches to oriented bounding boxes ...

Abstract: The rapid development of autonomous driving technology has driven continuous innovation in perception systems, with 4D millimeter-wave (mmWave) radar being one of the key sensing devices.

Abstract: Recent studies have integrated convolutions into transformers to introduce inductive bias and improve generalization performance. However, the static nature of conventional convolution ...

Abstract: Orthogonal frequency division multiplexing (OFDM)-based integrated sensing and communication (ISAC) is promising for future sixth-generation mobile communication systems. For OFDM-based ISAC ...

Abstract: Automatic medical image segmentation is a crucial topic in the medical domain and successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the most widespread ...

Abstract: The advent of modern communication systems has led to the widespread application of deep learning-based automatic modulation recognition (DL-AMR) in wireless communications. However, ...

Abstract: Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise information for diverse downstream applications. Recent development of the segment anything model ...