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Found 13 papers, 3 papers with code
Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label.
Advanced Intelligent Optimization Algorithms for Multi-Objective Optimal Power Flow in Future Power Systems: A Review
This review explores the application of intelligent optimization algorithms to Multi-Objective Optimal Power Flow (MOPF) in enhancing modern power systems.
Degradation Estimation Recurrent Neural Network with Local and Non-Local Priors for Compressive Spectral Imaging
In the Coded Aperture Snapshot Spectral Imaging (CASSI) system, deep unfolding networks (DUNs) have demonstrated excellent performance in recovering 3D hyperspectral images (HSIs) from 2D measurements.
The State of the Art in transformer fault diagnosis with artificial intelligence and Dissolved Gas Analysis: A Review of the Literature
Transformer fault diagnosis (TFD) is a critical aspect of power system maintenance and management.
Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging
However, in the data subproblem, the used sensing matrix is ill-suited for the real degradation process due to the device errors caused by phase aberration, distortion; in the prior subproblem, it is important to design a suitable model to jointly exploit both spatial and spectral priors.
Ranked #3 on
Spectral Reconstruction
on CAVE
Multi-scale Network with Attentional Multi-resolution Fusion for Point Cloud Semantic Segmentation
In this paper, we present a comprehensive point cloud semantic segmentation network that aggregates both local and global multi-scale information.
OmniFusion: 360 Monocular Depth Estimation via Geometry-Aware Fusion
In this paper, we propose a 360 monocular depth estimation pipeline, OmniFusion, to tackle the spherical distortion issue.
Ranked #6 on
Depth Estimation
on Stanford2D3D Panoramic
PanoDepth: A Two-Stage Approach for Monocular Omnidirectional Depth Estimation
In this paper, we propose a novel, model-agnostic, two-stage pipeline for omnidirectional monocular depth estimation.
Ranked #13 on
Depth Estimation
on Stanford2D3D Panoramic
SPNet: Multi-Shell Kernel Convolution for Point Cloud Semantic Segmentation
Experimental results show that SPConv is effective in local shape encoding, and our SPNet is able to achieve top-ranking performances in semantic segmentation tasks.
Fast Point Voxel Convolution Neural Network with Selective Feature Fusion for Point Cloud Semantic Segmentation
Each layer has two parallel branches, namely the voxel branch and the point branch.
The Semantic Mutex Watershed for Efficient Bottom-Up Semantic Instance Segmentation
Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label.
RED-NET: A Recursive Encoder-Decoder Network for Edge Detection
In this paper, we introduce RED-NET: A Recursive Encoder-Decoder Network with Skip-Connections for edge detection in natural images.
DeepLofargram: A Deep Learning based Fluctuating Dim Frequency Line Detection and Recovery
This paper investigates the problem of dim frequency line detection and recovery in the so-called lofargram.
