Efficient object identification and localization for image retrieval using query-by-region

Lee, Yong-Hwan; Kim, Bonam; Kim, Heung-Jun

doi:10.1016/j.camwa.2011.08.019

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…The selecte was yolov5m, a 365-layer PyTorch neuronal network. The mean average precision with a 0.5 intersection over union (IoU) was established as the parameter to be op Most of the images without objects (90%) were removed for this training to en integrity of the results [33]. Tables 3 and 4 show the hardware used, the training ters, and the result obtained, respectively.…”

Section: Dataset Validationmentioning

confidence: 99%

Dataset: Traffic Images Captured from UAVs for Use in Training Machine Vision Algorithms for Traffic Management

Rosende

Ghisler²,

Andrés

et al. 2022

Data

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A dataset of Spanish road traffic images taken from unmanned aerial vehicles (UAV) is presented with the purpose of being used to train artificial vision algorithms, among which those based on convolutional neural networks stand out. This article explains the process of creating the complete dataset, which involves the acquisition of the data and images, the labeling of the vehicles, anonymization, data validation by training a simple neural network model, and the description of the structure and contents of the dataset (which amounts to 15,070 images). The images were captured by drones (but would be similar to those that could be obtained by fixed cameras) in the field of intelligent vehicle management. The presented dataset is available and accessible to improve the performance of road traffic vision and management systems since there is a lack of resources in this specific domain.

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Section: Dataset Validationmentioning

confidence: 99%

Dataset: Traffic Images Captured from UAVs for Use in Training Machine Vision Algorithms for Traffic Management

Rosende

Ghisler²,

Andrés

et al. 2022

Data

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show abstract

“…So far, the region of interest, i.e. (ROI)-based query, among these is the most common method in research prototypes and commercial products [1,4,9,14,15,16,23,28]. Typically a query image contains not only the ROIs but also other irrelevant areas.…”

Section: Introductionmentioning

confidence: 99%

ROI image retrieval based on multiple features of mean shift and expectation–maximisation

Chen

Dahal

2015

Digital Signal Processing

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Invariant feature extraction for 3D model retrieval: An adaptive approach using Euclidean and topological metrics

Huang

et al. 2012

Computers & Mathematics with Applications

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Efficient object identification and localization for image retrieval using query-by-region

Cited by 6 publications

References 12 publications

Dataset: Traffic Images Captured from UAVs for Use in Training Machine Vision Algorithms for Traffic Management

Dataset: Traffic Images Captured from UAVs for Use in Training Machine Vision Algorithms for Traffic Management

ROI image retrieval based on multiple features of mean shift and expectation–maximisation

Invariant feature extraction for 3D model retrieval: An adaptive approach using Euclidean and topological metrics

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