Enhancing Aerial Object Detection with Selective Frequency Interaction Network

Engineering, Aerospace Engineering, Information Science, Computer Science, Artificial Intelligence,
aerial object detection   frequency-domain features   selective frequency interaction   convolutional neural networks   feature extraction   deep learning   computer vision  

Selective Frequency Interaction Network for Improved Aerial Object Detection Background and Problem Statement With the advancements in computer vision, aerial object detection has become a critical research focus in remote sensing. This task aims to identify targets such as vehicles or buildings from aerial images captured at varying angles and alt...

RADIFF: Controllable Diffusion Models for Radio Astronomical Maps Generation

Physics, Astrophysics, Information Science, Computer Science, Artificial Intelligence,
diffusion models   radio astronomy   data augmentation   generative models   semantic segmentation  

RaDiff: Controllable Diffusion Models for Radio Astronomical Map Generation” Comprehensive Academic News Analysis Background Introduction With the near completion of the Square Kilometer Array (SKA) telescope, radio astronomy is poised for revolutionary advancements in the study of the universe. Boasting unprecedented sensitivity and spatial resolu...

Unsupervised Domain Adaptation on Point Clouds via High-Order Geometric Structure Modeling

Information Science, Computer Science, Artificial Intelligence,
point clouds   unsupervised domain adaptation   high-order geometric structures   contrastive learning   self-supervised learning   3D vision   feature alignment  

High-Order Geometric Structure Modeling-Based Unsupervised Domain Adaptation for Point Clouds Research Background and Motivation Point cloud data is a key data form for describing three-dimensional spaces, widely used in real-world applications such as autonomous driving and remote sensing. Point clouds can capture precise geometric information, bu...

AugDiff: Diffusion-Based Feature Augmentation for Multiple Instance Learning in Whole Slide Image

Information Science, Computer Science, Artificial Intelligence, Medicine, Oncology,
feature augmentation   diffusion model   multiple instance learning   whole slide image   computational pathology   deep learning   image generation  

Diffusion-Based Feature Augmentation: A Novel Approach for Multiple Instance Learning in Whole Slide Images Academic Background and Research Motivation In computational pathology, effectively analyzing Whole Slide Images (WSIs) is a burgeoning area of research. WSIs are ultra-high-resolution images with a broad field of view and are widely employed...

Higher-Order Directed Community Detection by a Multiobjective Evolutionary Framework

Information Science, Computer Science, Artificial Intelligence,
higher-order community detection   directed networks   information flow   multiobjective optimization   network topology   evolutionary algorithm   motif density  

The paper, titled “Higher-Order Directed Community Detection by a Multiobjective Evolutionary Framework”, authored by Jing Xiao, Jing Cao, and Xiao-Ke Xu, was published in the IEEE Transactions on Artificial Intelligence in December 2024. The authors introduce a novel approach for detecting higher-order communities in directed networks, addressing ...

Cost-Efficient Feature Selection for Horizontal Federated Learning

Information Science, Computer Science, Artificial Intelligence,
Federated Learning   Feature Selection   Multiobjective Optimization   Mutual Information   Clustering  

Research on Cost-Efficient Feature Selection in Horizontal Federated Learning Background and Motivation As Federated Learning (FL) is increasingly recognized as a distributed machine learning paradigm that safeguards data privacy, its application to multi-client scenarios has garnered significant attention. In Horizontal Federated Learning (HFL), a...