One of the primary problems in military surveillance systems is the safety of the visual data gathered by the sensor nodes installed in the different areas of the Visual sensor network and the remotely operated device...
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Technology is continuously changing our life. Day by day, it makes our life easy, but some challenges and issues exist. Counterfeit currency is one of them. It happens because of the production and circulation of curr...
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Deblurring high resolution remote sensing image is a very important problem in remote sensing research. In this paper, we propose a new deblurring algorithm for high-resolution remote sensing images (HSI) based on spa...
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In computer vision and imageprocessing, image deblurring is a crucial phase that attempts to restore the sharpness of the image and clarity of images that have been damaged due to motion blur, defocus, or other facto...
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Ultrasonography (US) has demonstrated many advantages in the detection, characterization, and monitoring of different diseases. Through high frequency probes, it is possible to visualize and characterize the anatomica...
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ISBN:
(纸本)9798350319439
Ultrasonography (US) has demonstrated many advantages in the detection, characterization, and monitoring of different diseases. Through high frequency probes, it is possible to visualize and characterize the anatomical layers, such as tissues, which can constitute a very helpful supporting tool in several procedures, e.g., surgeries. However, the visual identification of tissues in this type of image is still a challenge for some professionals. In this work, we evaluate deep learning (DL) segmentation algorithms for the tissue segmentation task in US. Moreover, we briefly assess whether their performance can be improved by including a crowdsourcing step. In order to perform the segmentation task, different segmentation models are trained, as posteriorly, the crowdsourcing step is included. The proposed approach is composed of the following steps: 1- automatic segmentation using a deep learning algorithm;2 - crowd evaluation and correction of the results. In order to perform step 1, different segmentation models are trained. The second step includes a visual interface where users can: a) validate the quality of the automatic segmentation;or b) correct the segmentation whether the DL result is inconsistent. All users are scored, denoting the quality of their annotations, considering the manual annotations provided by an expert for a small group of images. In order to evaluate the method and compare it to a DL algorithms alone, a total of 100 US images were used. Our experiments show that the inclusion of crowdsourcing significantly improved the performance of the tissue segmentation task compared to using the DL models alone. The performance of our method demonstrated the feasibility of applying this type of solution for the considered problem of segmenting tissues in US facial images. Moreover, the results suggest that this tool can be employed as an auxiliary tool in oral procedures.
The number of newly diagnosed cases of breast cancer exceeds 2.3 million annually worldwide. There is a severe lack of valid prognostic and predictive indicators for the clinical treatment of breast cancer patients at...
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The retinal arteries separation and classification algorithms are one of the fundamental components of eye diseases diagnostic systems using imageprocessing. In other words, it can be said that morphological changes ...
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Infrared imaging provides a non-invasive and non-destructive technique which offers valuable insight into several fundamental research processes in which active thermal monitoring is essential [1][2]. Typically, one m...
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ISBN:
(纸本)9781510684942;9781510684959
Infrared imaging provides a non-invasive and non-destructive technique which offers valuable insight into several fundamental research processes in which active thermal monitoring is essential [1][2]. Typically, one major limitation of infrared imaging is a narrow, bracketed snapshot dynamic range. Complex Radiometric calibration schemes such as Telops global calibration allow for optimization of this snapshot dynamic range over time through automated integration adjustment, but are still limited to ranges on the order of similar to 150C for a given optical path and exposure time. As such Telops has developed a next generation mid-wave thermal infrared imaging system which improves the snapshot dynamic range to more than 900C for a single exposure time. Telops 'HDR M700' is a first of its kind system designed around a brand new 24-bit, 640x512 pixel SLS detector (20 mu m pixel pitch, 600Hz maximum in full frame operation) which features advanced on-chip architecture that enables real-time saturation management functionality.
This paper introduces a new dataset RWU3D that consists of ToF depth images and the corresponding amplitude images as well as high-resolution Stereo images and the respective ground truth data. The corresponding dispa...
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Recent years, both the domestic and international frontiers made headway in the realm of intelligent navigation for ships, so vision-based ship monitoring systems and smart ships had a great development prospect. Howe...
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