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Multi-object behaviour recognition based on object detection cascaded image classification in classroom scenes
For multi-object behaviour recognition in classroom scenes, crowded objects have heavy occlusion, invisible keypoints, scale variation, which...
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OV-DAR: Open-Vocabulary Object Detection and Attributes Recognition
In this paper, we endeavor to localize all potential objects in an image and infer their visual categories, attributes, and shapes, even in instances...
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Learning by Asking Questions for Knowledge-Based Novel Object Recognition
In real-world object recognition, there are numerous object classes to be recognized. Traditional image recognition methods based on supervised...
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Underwater occluded object recognition with two-stage image reconstruction strategy
The complex underwater environment, such as foreign object occlusion and dim light, causes the feature of underwater objects to be seriously missing....
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Saliency information and mosaic based data augmentation method for densely occluded object recognition
Data augmentation methods are crucial to improve the accuracy of densely occluded object recognition in the scene where the quantity and diversity of...
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Bridging realities: training visuo-haptic object recognition models for robots using 3D virtual simulations
This paper proposes an approach for training visuo-haptic object recognition models for robots using synthetic datasets generated by 3D virtual...
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Efficient 3D object recognition in mobile edge environment
3D object recognition has great research and application value in the fields of automatic drive, virtual reality, and commercial manufacturing....
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Text-driven object affordance for guiding grasp-type recognition in multimodal robot teaching
In robot teaching, the gras** strategies taught to robots by users are critical information, because these strategies contain the implicit...
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Robust object recognition via context-driven reliability assessment
Robust recognition of objects is crucial across various applications, spanning from industrial automation to healthcare and security. Nevertheless,...
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Complementary spatial transformer network for real-time 3D object recognition
Tiny Deep Learning Models offer many advantages in various applications. From the perspective of statistical machine learning theory the...
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Ownership of abandoned object detection by integrating carried object recognition and context sensing
Abandoned baggage poses a potential threat to public safety, which needs to be monitored to avoid catastrophic effects. Identifying left baggage, the...
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A deep learning model based on sequential object feature accumulation for sport activity recognition
Activity recognition is a problem of recognizing what activities are occurring within a video. An activity consists of the spatial movements of the...
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Accurate Fine-Grained Object Recognition with Structure-Driven Relation Graph Networks
Fine-grained object recognition (FGOR) aims to learn discriminative features that can identify the subtle distinctions between visually similar...
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UAV image object recognition method based on small sample learning
In recent years, unmanned aerial vehicles (UAVs) have developed rapidly. Because of their small size, low cost, and strong maneuverability, they have...
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Insights into aerial intelligence: assessing CNN-based algorithms for human action recognition and object detection in diverse environments
Today’s era follows a data-driven decision process for large-scale environment analysis. Aerial view-based decision process plays a key role in...
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MVContrast: Unsupervised Pretraining for Multi-view 3D Object Recognition
3D shape recognition has drawn much attention in recent years. The view-based approach performs best of all. However, the current multi-view methods...
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Oriented-tooth recognition using a five-axis object-detection approach
X-ray images are essential data sources for checking the condition of the teeth, gums, jaws, and bone structure of the mouth. Tooth recognition is...
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Human skeleton behavior recognition model based on multi-object pose estimation with spatiotemporal semantics
Multi-object pose estimation in surveillance scenes is challenging and inaccurate due to object motion blur and pose occlusion in video data....
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Hand-Drawn Electrical Circuit Recognition Using Object Detection and Node Recognition
With the recent developments in neural networks, there has been a resurgence in algorithms for the automatic generation of simulation ready...
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Human–object interaction recognition based on interactivity detection and multi-feature fusion
Human–object interaction (HOI) recognition is a computer vision task that detects the relationship between human and surrounding objects. Though...
