Mengkun Liu

Explicitly learning semantic relevance for salient object detection in remote sensing images

Tao Gao, Weiguang Zhao, Mengkun Liu, Ting Chen et autres

cn (code pays fourni par la source)

HP-Net: Hierarchical Pooling Interaction Network for RGB-D Salient Object Detection

Tao Gao, Weidong Zhao, Mengkun Liu, Ting Chen et autres

au (code pays fourni par la source)

A Lightweight Multifeature Hybrid Mamba for Remote Sensing Image Scene Classification

Huihui Dong, Jingcao Li, Zongfang Ma, Zhijie Li et autres

Remote sensing (RS) image scene classification has wide applications in the field of RS. Although existing methods have achieved remarkable performance, there are still limitations in feature extraction and lightweight design. Current multi-branch models, although performing well, have large parameter counts and …

cn (code pays fourni par la source)

Light suppression enhancement network for complex night traffic image enhancement

Xiao Wang, Mengkun Liu, Yuhan Cao, Tao Gao et autres

cn (code pays fourni par la source)

KCI-Net: Knowledge-Based Contourlet Inference Network for Super-Resolution

Mengkun Liu, Licheng Jiao, Xu Liu, Lingling Li et autres

Textural details are useful for image super-resolution, but massive CNN methods ignored the high-frequency components and generated over-smoothed outputs. The knowledge-based contourlet inference network is proposed in this paper. Different from other CNN-based methods that are directly infer high-resolution (HR) images, our …

cn, me (code pays fourni par la source)

Brain-Inspired Spiking Neural Networks for Energy-Efficient Object Detection

Ziqi Li, Tao Gao, Yisheng An, Ting Chen et autres

Brain-inspired spiking neural networks (SNNs) have the capability of energy-efficient processing of temporal information. However, leveraging the rich dynamic characteristics of SNNs and prior works in artificial neural networks (ANNs) to construct an effective object detection model for visual tasks remains an …

cn, au (code pays fourni par la source)

Cross-Level Interaction and Intralevel Fusion Network for Remote Sensing Image Dehazing

Yuanbo Wen, Tao Gao, Ting Chen, Ziqi Li et autres

Existing approaches have significantly advanced remote sensing image dehazing. However, they often rely on conventional encoder-decoder architectures, leading to prolonged inference times. To this end, we propose a novel cross-level interaction and intra-level fusion network for remote sensing image dehazing (CINet), which …

cn (code pays fourni par la source)

MSNet: Multi-Scale Network for Object Detection in Remote Sensing Images

Tao Gao, Mengkun Liu, Jing Zhang, Ting Chen et autres

cn, au (code pays fourni par la source)

$C^{2}N^{2}$: Complex-Valued Contourlet Neural Network

Mengkun Liu, Licheng Jiao, Xu Liu, Lingling Li et autres

Complex-valued convolutional neural networks (CV-CNN) have recently gained recognition in feature representation learning. It implements the repeated application of the operations in convolution, local average pooling, and the absolute value of the resulting vectors. However, it is only conducted in the complex …

cn (code pays fourni par la source)

Multi-Scale Contourlet Knowledge Guide Learning Segmentation

Mengkun Liu, Licheng Jiao, Xu Liu, Lingling Li et autres

For accurate segmentation, effective feature extraction has always been a challenging problem, since the variability of appearance and the fuzziness of object boundaries. Convolutional neural networks have recently gained recognition in feature representation learning. However, it is only conducted in the spatial …

cn (code pays fourni par la source)

Bio-Inspired Multi-Scale Contourlet Attention Networks

Mengkun Liu, Licheng Jiao, Xu Liu, Lingling Li et autres

Inspired by the sparse and hierarchical features representation in the ventral stream of the human visual system, the biologically inspired multi-scale contourlet attention network (BMCAnet) is proposed to extract robust discriminative features. First, we constructed the multi-scale contourlet filter banks as a …

cn (code pays fourni par la source)

Audio-Visual Affect Recognition

Zhitao Zeng, J. Tu, Mengkun Liu, Thomas S. Huang et autres

The ability of a computer to detect and appropriately respond to changes in a user's affective state has significant implications to human-computer interaction (HCI). In this paper, we present our efforts toward audio-visual affect recognition on 11 affective states customized for HCI …

us (code pays fourni par la source)