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A Dark and Bright Channel Prior Guided Deep Network for Retinal Image Quality Assessment [article]

Ziwen Xu, Beiji Zou, Qing Liu
2021 arXiv   pre-print
This paper proposes a dark and bright channel prior guided deep network for retinal image quality assessment called GuidedNet.  ...  In addition, we re-annotate a new retinal image quality dataset called RIQA-RFMiD for further validation.  ...  CONCLUSION This paper presents a simple framework for retina image quality assessment. It introduces dark and bright channel priors to predict image quality.  ... 
arXiv:2010.13313v2 fatcat:gyyvy772ofdwva3cqgxavw3q6e

Guest editorial: special issue on Web and big data 2019

Jie Shao, Man Lung Yiu, Toyoda Masashi
2020 World wide web (Bussum)  
The fourth paper, "A Framework for Image Dark Data Assessment", presents an assessment framework combining deep learning, hash technique and graph-based computing, which helps users to detect the potential  ...  value of image dark data and avoid unnecessary mining cost.  ... 
doi:10.1007/s11280-020-00797-9 fatcat:wqzofivdjfcc5puqteaka2f4lm

S- and X-band SAR data fusion

Raffaella Guida, Su Wai Ng, Pasquale Iervolino
2015 2015 IEEE 5th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR)  
This paper investigates the benefits deriving from introducing a wavelet-transform-based fusion framework for multi-frequency Synthetic Aperture Radar (SAR) data.  ...  A specific application is considered in the assessment of the fused classification map derived and this is the discrimination of different kinds of oil in sea.  ...  ACKNOWLEDGMENT The authors thank the Satellite Application Catapult for making the data from the oil on water exercise available for this study and Airbus Defence and Space and NERC for providing, respectively  ... 
doi:10.1109/apsar.2015.7306275 fatcat:b5slfv45v5durodpiv5ue3mvem

Automated tumor assessment of squamous cell carcinoma on tongue cancer patients with hyperspectral imaging

Francesca Manni, Fons van der Sommen, Sveta Zinger, Esther Kho, Susan G. Brouwer de Koning, Theo J. M. Ruers, Caifeng Shan, Jean Schleipen, Peter H. N. de With, Cristian A. Linte, Baowei Fei
2019 Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling  
This feasibility study paves the way for introducing HSI as a non-invasive imaging aid for cancer detection and increase of the effectiveness of surgical oncology.  ...  The proposed solution forms a novel framework for automated tongue-cancer detection, explicitly exploiting HSI, which particularly uses the spectral variations in specific bands describing the cancerous  ...  First, the raw image data and white reference images are normalized, in order to correct for the dark current influence and illumination intensity differences.  ... 
doi:10.1117/12.2512238 dblp:conf/miigp/ManniSZKKRSSW19 fatcat:nsm7lqplnnh4nnnjsnfpscj3zq

Print Defect Mapping with Semantic Segmentation [article]

Augusto C. Valente, Cristina Wada, Deangela Neves, Deangeli Neves, Fábio V. M. Perez, Guilherme A. S. Megeto, Marcos H. Cascone, Otavio Gomes, Qian Lin
2020 arXiv   pre-print
We use synthetic training data by simulating two types of print defects and a print-scan effect with image processing and computer graphic techniques.  ...  Our model is evaluated on a dataset of real printed images.  ...  Acknowledgements We thank Eric Maggard from HP Inc. at Boise, ID for providing the image dataset with real print defects, and Jianyu Wang, Terry Nelson, Renee Jessome, Steve Astling, Eric Maggard, Mark  ... 
arXiv:2001.10111v1 fatcat:wmluvcyz4jbhfmpowxfx53rvzy

Print Defect Mapping with Semantic Segmentation

Augusto C. Valente, Cristina Wada, Deangela Neves, Deangeli Neves, Fabio V. M. Perez, Guilherme A. S. Megeto, Marcos H. Cascone, Otavio Gomes, Qian Lin
2020 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)  
We use synthetic training data by simulating two types of print defects and a print-scan effect with image processing and computer graphic techniques.  ...  Our model is evaluated on a dataset of real printed images.  ...  Acknowledgements We thank Eric Maggard from HP Inc. at Boise, ID for providing the image dataset with real print defects, and Jianyu Wang, Terry Nelson, Renee Jessome, Steve Astling, Eric Maggard, Mark  ... 
doi:10.1109/wacv45572.2020.9093470 dblp:conf/wacv/ValenteWNNPMCGL20 fatcat:h53sekptzfamvggevmedzjvfqi

Single image haze removal considering sensor blur and noise

Xia Lan, Liangpei Zhang, Huanfeng Shen, Qiangqiang Yuan, Huifang Li
2013 EURASIP Journal on Advances in Signal Processing  
Experimental results with both simulated and real data demonstrate that the proposed algorithm is effective, based on both the visual effect and quantitative assessment.  ...  Therefore, in this paper, a three-stage algorithm for haze removal, considering sensor blur and noise, is proposed.  ...  This dark channel prior method is a major breakthrough for haze removal from a single image and is the state of the art until now.  ... 
doi:10.1186/1687-6180-2013-86 fatcat:orufsgrnfzdpja7an2dcwlxj3i

Sea State Primitive Object Creation from SAR Data

Konstantinos Topouzelis, Dimitra Kitsiou
2014 International journal of geosciences  
Dark areas were initially detected in SAR images using thresholds, adapted or not. Afterwards, SAR images were normalized and a global threshold was calculated for each image.  ...  Images were segmented and objects were created for each dark area. The results were compared to a reference dataset created from theoretical modeled values and extracted in a GIS environment.  ...  The authors would also like to thank the European Space Agency (ESA) which provided the ENVISAT ASAR data for the study within their PI program.  ... 
doi:10.4236/ijg.2014.513127 fatcat:5t5fhoydo5d7bls5ie3pqqy7q4

Automated Image Processing to Quantify Cell Migration [chapter]

Minmin Shen, Bastian Zimmer, Marcel Leist, Dorit Merhof
2013 Bildverarbeitung für die Medizin 2013  
Based on an image captured only once at the end of the biological experiment, the framework identifies the initial ROI.  ...  Here, we established an automated image processing framework to quantify migration of human neural crest (NC) cells into an initially empty, circular region of interest (ROI) .  ...  The acquisition of image data and the image processing framework are elaborated in Section 2. The results are shown in Section 3 to demonstrate the validity of the proposed framework.  ... 
doi:10.1007/978-3-642-36480-8_28 dblp:conf/bildmed/ShenZLM13 fatcat:6rhjijbwvfbd5fljdhvrfomvby

An Object-Based Semantic Classification Method for High Resolution Remote Sensing Imagery Using Ontology

Haiyan Gu, Haitao Li, Li Yan, Zhengjun Liu, Thomas Blaschke, Uwe Soergel
2017 Remote Sensing  
for remote sensing data discovery, multi-source data integration, image interpretation, workflow management and knowledge sharing [19].  ...  Kohli et al. (2012) provided a comprehensive framework that includes all potentially relevant indicators that can be used for image-based slum identification [22].  ...  A comprehensive accuracy assessment was carried out. A sample-based error matrix is created and used for performing accuracy assessment. In GEOBIA, a sample refers to an object.  ... 
doi:10.3390/rs9040329 fatcat:lvhb5yrukzdfvdc6zzjil57g3a

Image Analysis Techniques For Cultural Heritage Restoration Methods Evaluation

Oana Loredana Buzatu, Bogdan Goras, Liviu Goras, Emil Ghiocel Ioanid
2012 Zenodo  
The data set (images) acquisition system was placed in a dark room and consisted in a digital camera with 35 mm f/3.5 macro lens and four halogen lamps.  ...  For the statistical measurements mean value and standard deviation, as for the image quality assessment index BIQI, average values over the entire image patches data set at every treatment stage have been  ... 
doi:10.5281/zenodo.52428 fatcat:tpjbytx4mzcqvph6rjjcjdyqg4

ConiVAT: Cluster Tendency Assessment and Clustering with Partial Background Knowledge [article]

Punit Rathore, James C. Bezdek, Paolo Santi, Carlo Ratti
2020 arXiv   pre-print
The VAT method is a visual technique for determining the potential cluster structure and the possible number of clusters in numerical data.  ...  We demonstrate ConiVAT approach to visual assessment and single linkage clustering on nine datasets to show that, it improves the quality of iVAT images for complex datasets, and it also overcomes the  ...  ) iVAT for N = Data scatterplot, VAT, and iVAT images for a 2D synthetic dataset.  ... 
arXiv:2008.09570v2 fatcat:yuh2q6rwevf77c52f72xszqceu

Image-color-quality modeling under various surround conditions for a 2-in. mobile transmissive LCD

Youn-Jin Kim, M. Ronnier Luo, Peter Rhodes, Won-Hee Choe, Seong-Deok Lee, Seung-Sin Lee, Young-Shin Kwak, Dus-Sik Park, Chang-Yeong Kim
2007 Journal of the Society for Information Display  
contrast -Assessment of ICQ model under various surround conditions • Dark condition and three outdoor condition 2/25  ...   Modeling cognitive Image color quality under various surround conditions -Local adaptation process • Using Memory color reproduction ratio(MCRR) -Global adaptation process • Using colorfulness and luminance  ...  data [ ] 2 2 2 2 2 2 2 2 2 2 2 m c L Q a b c d e f g m c L mcL           = ×             (6)  Hypothetical framework for ICQ judgement -Using ROI for modeling Local adaptation  ... 
doi:10.1889/1.2785202 fatcat:cldufeohovewvce2byq3jnyr5e

Counteracting Dark Web Text-Based CAPTCHA with Generative Adversarial Learning for Proactive Cyber Threat Intelligence [article]

Ning Zhang, Mohammadreza Ebrahimi, Weifeng Li, Hsinchun Chen
2022 arXiv   pre-print
In this study, we propose a novel framework for automated breaking of dark web CAPTCHA to facilitate dark web data collection.  ...  While there are efficient methods for collecting data from the surface web, large-scale dark web data collection is often hindered by anti-crawling measures.  ...  We demonstrate the applicability of our proposed framework through a case study on dark web data collection, where we incorporated our framework into a dark web crawler.  ... 
arXiv:2201.02799v2 fatcat:nepnavt6onaf7ncinm2x6ar5ey

Assessing the Health of the Dark Web: [chapter]

Samuel Onyango, Emilie Steenvoorden, Joram Scholten, Slinger Jansen
2021 Lecture Notes in Business Information Processing  
The Open Source Ecosystem Health Operationalization framework is used to help perform this assessment. Eight metrics from the framework are selected, which are measured using the data collected.  ...  The framework proves to be adequately capable of determining the health of the Dark Web open source ecosystem with the available data.  ...  Step 4 -Assess and Collect Data This section covers an assessment of data requirements and the applied data collection techniques for all metrics.  ... 
doi:10.1007/978-3-030-88583-0_12 fatcat:uouijaypkjeojc5sndhj6aobp4
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