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Fast camouflaged object detection via multi-scale feature-enhanced network
The aim of camouflaged object detection (COD) is to identify objects that are hidden or camouflaged in the visual scene. Since camouflaged objects...
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MFMANet: a multispectral pedestrian detection network using multi-resolution RGB feature reuse with multi-scale FIR attentions
In the realm of multispectral pedestrian detection, especially under challenging low-illumination, the existing methods, characterized by...
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MADMM: microservice system anomaly detection via multi-modal data and multi-feature extraction
Accurately detecting anomalies in microservice systems is crucial to avoid system failures and economic losses for users. Existing approaches detect...
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Feature refinement with multi-level context for object detection
Robust multi-scale object detection is challenging as it requires both spatial details and semantic knowledge to deal with problems including high...
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Multi-branch feature fusion and refinement network for salient object detection
With the development of convolutional neural networks (CNNs), salient object detection methods have made great progress in performance. Most methods...
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Small target detection algorithm for printing defects detection based on context structure perception and multi-scale feature fusion
Small target detection is an important research direction in the field of computer vision, which is widely used in popular fields such as industrial...
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Salient feature fusion convolutional network for multi-class meters detection
Automatic meter reading via deep learning and computer vision have become feasible for ensuring safe and stable substation operation. Meter model...
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A multi-level feature attention network for COVID-19 detection based on multi-source medical images
Chest X-ray and CT are the effective imaging techniques that provide a non-invasive tool to monitor the progression of the COVID-19 that has raged...
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SAR ship detection network based on global context and multi-scale feature enhancement
With the rapid development of synthetic aperture radar (SAR) technology, SAR image ship detection plays a crucial role in fields such as marine...
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Enhanced deep transfer learning with multi-feature fusion for lung disease detection
Early detection of lung disease is important for timely intervention and treatment, enhancing patient outcomes and decreasing healthcare cost. Chest...
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Multi-scale feature fusion with attention mechanism for crowded road object detection
Crowded object detection under the heavy traffic environment is always a challenging task in the field of autonomous driving and robotics, because...
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MVTr: multi-feature voxel transformer for 3D object detection
Convolutional neural networks have become a powerful tool for partial 3D object detection. However, their power has not been fully realized for...
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Multi-food detection using a modified swin-transfomer with recursive feature pyramid network
Humans need food, and the food detection system is a fascinating research topic and a complex weight loss mechanism. Eating healthy and balanced is...
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PCDR-DFF: multi-modal 3D object detection based on point cloud diversity representation and dual feature fusion
Recently, multi-modal 3D object detection techniques based on point clouds and images have received increasing attention. However, existing methods...
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IMSFNet: integrated multi-source feature network for salient object detection
Multi-scale context features are conducive to image understanding, so it plays an important role in salient object detection (SOD) tasks, and...
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Multi-scale aggregation feature pyramid with cornerness for underwater object detection
Underwater object detection is a fascinating but challengeable subject in computer vision. Features are difficult to extract due to the color cast...
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A multi-classification detection model for imbalanced data in NIDS based on reconstruction and feature matching
With the exponential growth of various data interactions on network systems, network intrusions are also increasing. The emergence of edge computing...
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Residual attention mechanism and weighted feature fusion for multi-scale object detection
Object detection is one of the critical problems in computer vision research, which is also an essential basis for understanding high-level semantic...
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Multi-view change detection method for mechanical assembly images based on feature fusion and feature refinement with depthwise separable convolution
Accurately monitoring the assembly sequence of mechanical parts is significant for reducing assembly process errors and improving assembly accuracy....
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Real-time detection algorithm for digital meters based on multi-scale feature fusion and GCS
Aiming at the problems of insufficient feature fusion, large number of network parameters and low target saliency in the current digital meter...
