ArticleFrontiers in neurorobotics2022
Multi-Scale Feature Fusion Convolutional Neural Network for Indoor Small Target Detection.
Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed.
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- RFCS-YOLO: Target Detection Algorithm in Adverse Weather Conditions via Receptive Field Enhancement and Cross-Scale Fusion.Sensors (Basel, Switzerland) · 2025Article
- MDE-DETR: multi-domain enhanced feature fusion algorithm for bayberry detection and counting in complex orchards.Frontiers in plant science · 2025Article
- Extended dipeptide composition framework for accurate identification of anticancer peptides.Scientific reports · 2024Article
- Artificial-Intelligence-Enhanced Analysis of In Vivo Confocal Microscopy in Corneal Diseases: A Review.Diagnostics (Basel, Switzerland) · 2024Review
- Dual assurance for healthcare and future education development: normalized assistance for low-income population in rural areas-evidence from the population identification.Frontiers in public health · 2024Article
- APM-YOLOv7 for Small-Target Water-Floating Garbage Detection Based on Multi-Scale Feature Adaptive Weighted Fusion.Sensors (Basel, Switzerland) · 2023Article
- Metal surface defect detection based on improved YOLOv5.Scientific reports · 2023Article
- A Tiny Object Detection Approach for Maize Cleaning Operations.Foods (Basel, Switzerland) · 2023Article
- Small object intelligent detection method based on adaptive recursive feature pyramid.Heliyon · 2023Article
- Detection of citrus diseases in complex backgrounds based on image-text multimodal fusion and knowledge assistance.Frontiers in plant science · 2023Article
- E-YOLOv4-tiny: a traffic sign detection algorithm for urban road scenarios.Frontiers in neurorobotics · 2023Article
- Multi-Objective Location and Mapping Based on Deep Learning and Visual Slam.Sensors (Basel, Switzerland) · 2022Article
- A siamese network-based approach for vehicle pose estimation.Frontiers in bioengineering and biotechnology · 2022Article
- VSLAM method based on object detection in dynamic environments.Frontiers in neurorobotics · 2022Article
- Multi-network collaborative lift-drag ratio prediction and airfoil optimization based on residual network and generative adversarial network.Frontiers in bioengineering and biotechnology · 2022Article
- Biomimetic Vision for Zoom Object Detection Based on Improved Vertical Grid Number YOLO Algorithm.Frontiers in bioengineering and biotechnology · 2022Article
- Detection method of wheat spike improved YOLOv5s based on the attention mechanism.Frontiers in plant science · 2022Article
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8 authors.
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Abstract
The development of object detection technology makes it possible for robots to interact with people and the environment, but the changeable application scenarios make the detection accuracy of small and medium objects in the practical application of object detection technology low. In this paper, based on multi-scale feature fusion of indoor small target detection method, using the device to collect different indoor images with angle, light, and shade conditions, and use the image enhancement technology to set up and amplify a date set, with indoor scenarios and the SSD algorithm in target detection layer and its adjacent features fusion. The Faster R-CNN, YOLOv5, SSD, and SSD target detection models based on multi-scale feature fusion were trained on an indoor scene data set based on transfer learning. The experimental results show that multi-scale feature fusion can improve the detection accuracy of all kinds of objects, especially for objects with a relatively small scale. In addition, although the detection speed of the improved SSD algorithm decreases, it is faster than the Faster R-CNN, which better achieves the balance between target detection accuracy and speed.
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