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Related Concept Videos

Vector Functions and Motion: Problem Solving01:30

Vector Functions and Motion: Problem Solving

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Related Experiment Video

Updated: Jun 12, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Coordinate aware implicit neural representation for UAV small object detection.

Yong Yang1, Tianci Wan1, Ling Guo2

  • 1School of Computer Science, Zhengzhou University of Aeronautics, Zhengzhou, China.

Plos One
|June 10, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel Coordinate-Aware Implicit Neural Representation (C2INR) module to improve small object detection in drone imagery. The C2INR enhances spatial details and localization accuracy, outperforming existing methods with minimal computational cost.

Related Experiment Videos

Last Updated: Jun 12, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments
03:31

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

Area of Science:

  • Computer Vision
  • Machine Learning
  • Artificial Intelligence

Background:

  • Small object detection in Unmanned Aerial Vehicle (UAV) imagery is difficult due to low resolution and complex backgrounds.
  • Conventional Convolutional Neural Network (CNN) detectors struggle with fine-grained spatial details and geometric relationships.

Purpose of the Study:

  • To propose a Coordinate-Aware Implicit Neural Representation Enhanced (C2INR) module for improved small object detection.
  • To enhance spatial continuity, geometric fidelity, and localization precision in UAV imagery.

Main Methods:

  • Integration of coordinate-based representations into convolutional feature extraction using the C2INR module.
  • Utilizing a Multi-Scale Coordinate Encoder (MSCE) with sinusoidal encoding for frequency-aware positional embeddings.
  • Employing an INR Feature Enhancer (IFE) and a Small Object Attention mechanism to fuse coordinates with visual features and focus on tiny targets.

Main Results:

  • Consistent improvements in small object detection accuracy across AI-TOD, UAVDT, and VisDrone benchmarks.
  • Demonstrated minimal computational overhead compared to existing methods.
  • Verified strong cross-domain generalization capabilities on the PASCAL VOC dataset.

Conclusions:

  • Coordinate-aware implicit representation offers an effective solution for enhancing spatial continuity and localization precision in small object detection.
  • The proposed C2INR module significantly improves performance on challenging UAV datasets.
  • The approach shows broad applicability and strong generalization for detecting small objects.