ASCDet: cross-space UAV object detection method guided by adaptive sparse convolution
Sign Up to like & getrecommendations! Published in 2025 at "International Journal of Digital Earth"
DOI: 10.1080/17538947.2025.2528648
Abstract: ABSTRACT UAV object detection, a critical aspect of remote sensing applications, faces challenges due to high object sparsity and complex backgrounds, leading to excessive computational demands. To address these issues, we propose the Cross-Space UAV… read more here.
Keywords: detection; cross space; object detection; sparse convolution ... See more keywords
Weighted Sparse Convolution and Transformer Feature Aggregation Networks for 3D Dental Segmentation
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3462521
Abstract: The conventional alginate technique, widely employed in dentistry to capture tooth morphology, has faced challenges, particularly due to potential discomfort and the risk of allergy reactions among specific patient groups. Consequently, 3D intraoral scanners (IOS),… read more here.
Keywords: segmentation; sparse convolution; weighted sparse; feature ... See more keywords
PTC-Net: Point-Wise Transformer With Sparse Convolution Network for Place Recognition
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Robotics and Automation Letters"
DOI: 10.1109/lra.2023.3267693
Abstract: In the point-cloud-based place recognition area, the existing hybrid architectures combining both convolutional networks and transformers have shown promising performance. They mainly apply the voxel-wise transformer after the sparse convolution (SPConv). However, they can induce… read more here.
Keywords: wise; point; sparse convolution; transformer sparse ... See more keywords
OPASCA: Outer Product-Based Accelerator With Unified Architecture for Sparse Convolution and Attention
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"
DOI: 10.1109/tcad.2024.3483092
Abstract: Vision transformer (ViT)-based models have achieved state-of-the-art accuracy in many computer vision tasks, but their attention mechanism is more computation and communication intensive than convolutional neural networks (CNNs). To adapt ViT-based models for resource-constrained edge… read more here.
Keywords: outer product; sparse convolution; convolution; attention ... See more keywords
A Sparse Convolution Method to Reduce the Atmospheric Phase Screen of SAR Interferometry in the Coastal Region
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2024.3465667
Abstract: Effective mitigation of atmospheric phase screen (APS) is crucial for synthetic aperture radar (SAR) interferometry in coastal regions. However, existing methods suffer from various limitations in estimating atmospheric delays, especially turbulent mixing components. As a… read more here.
Keywords: sar interferometry; method; sparse convolution; phase screen ... See more keywords
High-efficiency sparse convolution operator for event-based cameras
Sign Up to like & getrecommendations! Published in 2025 at "Frontiers in Neurorobotics"
DOI: 10.3389/fnbot.2025.1537673
Abstract: Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in various robotic applications. However, despite their inherent… read more here.
Keywords: sparse convolution; operator; event based; based cameras ... See more keywords
Integrating Contextual Information and Attention Mechanisms with Sparse Convolution for the Extraction of Internal Objects within Buildings from Three-Dimensional Point Clouds
Sign Up to like & getrecommendations! Published in 2024 at "Buildings"
DOI: 10.3390/buildings14030636
Abstract: Deep learning-based point cloud semantic segmentation has gained popularity over time, with sparse convolution being the most prominent example. Although sparse convolution is more efficient than regular convolution, it comes with the drawback of sacrificing… read more here.
Keywords: information; convolution; sparse convolution; point ... See more keywords
TSPconv-Net: Transformer and Sparse Convolution for 3D Instance Segmentation in Point Clouds
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12182926
Abstract: Current deep learning approaches for indoor 3D instance segmentation often rely on multilayer perceptrons (MLPs) for feature extraction. However, MLPs struggle to effectively capture the complex spatial relationships inherent in 3D scene data. To address… read more here.
Keywords: instance segmentation; sparse convolution; tspconv net; feature extraction ... See more keywords