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Found 11 papers, 6 papers with code
DUE: A Deep Learning Framework and Library for Modeling Unknown Equations
Recent advancements in machine learning and data science offer a new paradigm for modeling unknown equations from measurement or simulation data.
CFMD: Dynamic Cross-layer Feature Fusion for Salient Object Detection
Cross-layer feature pyramid networks (CFPNs) have achieved notable progress in multi-scale feature fusion and boundary detail preservation for salient object detection.
IU4Rec: Interest Unit-Based Product Organization and Recommendation for E-Commerce Platform
These IUs are then integrated into the Recommendation system, delivering both product and technological innovations.
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
Operator learning for Partial Differential Equations (PDEs) is rapidly emerging as a promising approach for surrogate modeling of intricate systems.
Deep-OSG: Deep Learning of Operators in Semigroup
It is a sequel to the previous flow map learning (FML) works [T. Qin, K. Wu, and D. Xiu, J. Comput.
Abnormal Occupancy Grid Map Recognition using Attention Network
The occupancy grid map is a critical component of autonomous positioning and navigation in the mobile robotic system, as many other systems' performance depends heavily on it.
FEANet: Feature-Enhanced Attention Network for RGB-Thermal Real-time Semantic Segmentation
To better extract detail spatial information, we propose a two-stage Feature-Enhanced Attention Network (FEANet) for the RGB-T semantic segmentation task.
Ranked #14 on
Semantic Segmentation
on FMB Dataset
AcousticFusion: Fusing Sound Source Localization to Visual SLAM in Dynamic Environments
Dynamic objects in the environment, such as people and other agents, lead to challenges for existing simultaneous localization and mapping (SLAM) approaches.
A Two-stage Unsupervised Approach for Low light Image Enhancement
However, most of them suffer from the following problems: 1) the need of pairs of low light and normal light images for training, 2) the poor performance for dark images, 3) the amplification of noise.
Low-Light Image Enhancement
Simultaneous Localization and Mapping
+1
Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment
The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL).
U-net architectures for fast prediction of incompressible laminar flows
Machine learning is a popular tool that is being applied to many domains, from computer vision to natural language processing.
Computational Physics Image and Video Processing
