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Crack Detection and Comparison Study Based on Faster R-CNN and Mask R-CNN [PDF]
Sensors, 2022 The intelligent crack detection method is an important guarantee for the realization of intelligent operation and maintenance, and it is of great significance to traffic safety.
Xiangyang Xu +6 more
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Lightweight faster R-CNN for object detection in optical remote sensing images [PDF]
Scientific ReportsVarious applications in remote sensing rely on object detection approaches, such as urban detection, precision farming, and disaster prediction. Faster RCNN has gained popularity for its performance but comes with significant computational and storage ...
Andrew Magdy +3 more
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Face Detection with the Faster R-CNN [PDF]
2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), 2016 The Faster R-CNN has recently demonstrated impressive results on various object detection benchmarks. By training a Faster R-CNN model on the large scale WIDER face dataset, we report state-of-the-art results on two widely used face detection benchmarks,
Jiang, Huaizu, Learned-Miller, Erik
core +4 more sources
An OpenCL-Based FPGA Accelerator for Faster R-CNN [PDF]
Entropy, 2022 In recent years, convolutional neural network (CNN)-based object detection algorithms have made breakthroughs, and much of the research corresponds to hardware accelerator designs. Although many previous works have proposed efficient FPGA designs for one-
Jianjing An +3 more
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MS-Faster R-CNN: Multi-Stream Backbone for Improved Faster R-CNN Object Detection and Aerial Tracking from UAV Images [PDF]
Remote Sensing, 2021 Tracking objects across multiple video frames is a challenging task due to several difficult issues such as occlusions, background clutter, lighting as well as object and camera view-point variations, which directly affect the object detection.
Danilo Avola +7 more
doaj +4 more sources
Future TransportationThe Faster Region-based Convolutional Network (Faster R-CNN) is an efficient object detection model. However, its large size and significant computational requirements limit its applicability in embedded systems and real-time environments.
Tamás Menyhárt, Róbert Lakatos
doaj +2 more sources
Deep Learning-Based Dental Caries Diagnosis: A Modality-Stratified Systematic Review and Meta-Analysis of Faster R-CNN and Mask R-CNN [PDF]
DiagnosticsBackground: Deep convolutional neural networks (DCNNs) are increasingly used in computer-aided dental diagnostics. However, the relative diagnostic performance of commonly applied architectures, particularly Faster R-CNN and Mask R-CNN, has not been ...
Quang Tuan Lam +4 more
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Improved Faster R-CNN for the Detection Method of Industrial Control Logic Graph Recognition [PDF]
Frontiers in Bioengineering and Biotechnology, 2022 In the process of developing the industrial control SAMA logic diagram commonly used in the industrial process control system, there are some problems, that is, the size of logic diagram elements is small, the shape is various, similar element ...
Shilin Wu +4 more
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Joint embedding VQA model based on dynamic word vector [PDF]
PeerJ Computer Science, 2021 The existing joint embedding Visual Question Answering models use different combinations of image characterization, text characterization and feature fusion method, but all the existing models use static word vectors for text characterization.
Zhiyang Ma +3 more
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Object Detection Techniques: A Review
Wasit Journal of Computer and Mathematics Science, 2023 Humans can understand their surroundings clearly because they regularly notice objects in their environment. It is essential for the machine to perceive the surroundings similarly to how humans do in order to make it autonomous and capable of navigating
Widad K. Mohammed +3 more
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