GitHub

VeloxSeg: Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

Overview of VeloxSeg. VeloxSeg employs an encoder-decoder architecture with Paired Window Attention (PWA) and Johnson-Lindenstrauss lemma-guided convolution (JLC) on the left, using 1x1 convolution as ...
IEEE

Rethinking Fast Fourier Convolution in Image Inpainting

Abstract: Recently proposed LaMa [25] introduce Fast Fourier Convolution (FFC) [4] into image inpainting. FFC empowers the fully convolutional network to have a global receptive field in its early ...
IEEE

Depthwise Convolution with Winograd Algorithm for Efficient CNN Acceleration

This work explores an efficient convolutional acceleration framework tailored for edge devices by integrating Depthwise Convolution with the Winograd algorithm. Through RTL-based hardware ...
IEEE

Deformable Convolution-Guided Multiscale Feature Learning and Fusion for UAV Object Detection

Abstract: Object detection (OD) in unmanned aerial vehicle (UAV) images faces many challenges, with diverse-scale objects and small objects being particularly prominent issues. To alleviate these ...
IEEE

Graph Convolution Neural Network Based End-to-End Channel Selection and Classification for Motor Imagery Brain–Computer Interfaces

Abstract: Classification of electroencephalogram-based motor imagery (MI-EEG) tasks is crucial in brain–computer interface (BCI). EEG signals require a large number of channels in the acquisition ...
IEEE

A 28nm 2D/3D Unified Sparse Convolution Accelerator with Block-Wise Neighbor Searcher for Large-Scaled Voxel-Based Point Cloud Network

Abstract: 3D processing plays an important role in many emerging applications such as autonomous driving, visual navigation and virtual reality. Recent research shows that adopting 3D voxel-based ...
IEEE

Heterogeneous Spatiotemporal Graph Convolution Network for Multi-Modal Wind-PV Power Collaborative Prediction

Abstract: Accurate and generalized collaborative prediction of multi-cluster renewable energy power generation is both an inevitable trend and urgent demand as the growth of multi-region ...
IEEE

B1D–CNN: A Novel Convolution Neural Network-Based Chlorophyll-A Retrieval Algorithm for Sentinel–2 Data

Abstract: Deep learning (DL) methods have been recently considered suitable for Chlorophyll-a (Chla) retrieval from satellite data due to their ability for handling complex, high-dimensional, and ...
IEEE

Mixing Self-Attention and Convolution: A Unified Framework for Multisource Remote Sensing Data Classification

Abstract: Convolution and self-attention are two powerful techniques for multisource remote sensing (RS) data fusion that have been widely adopted in Earth observation tasks. However, convolutional ...
IEEE

SKGNet: Robotic Grasp Detection With Selective Kernel Convolution

Abstract: Real-time and accuracy are important evaluation metrics of robotic grasp detection algorithms. To further improve the accuracy on the premise of ensuring real-time performance, in this paper ...
IEEE

A Multiview Sparse Dynamic Graph Convolution-Based Region-Attention Feature Fusion Network for Major Depressive Disorder Detection

Abstract: Detecting and diagnosing major depressive disorder (MDD) is greatly crucial for appropriate treatment and support. In recent years, there have been efforts to develop automated methods for ...
IEEE

CCFT: The Convolution and Cross-Fusion Transformer for Fault Diagnosis of Bearings

Abstract: A single-vibration signal is no longer adequate to fulfill the requirements of intelligent fault diagnosis (IFD) of bearings in complex systems. With the rapid advancement of the industrial ...