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1 Chapter Cancel anytime Subscribe now Buy Now Price excludes VAT (USA) Tax calculation will be finalised during checkout. Instant access to the full article PDF. Similar content being viewed by others ReferencesAmerini I, Ballan L, Caldelli R, Del Bimbo A, Serra G (2011) A sift-based forensic method for copy–move attack detection and transformation recovery. IEEE Trans. Inf. Forensics Secur. 6:1099–1110Article Google Scholar Amerini I, Ballan L, Caldelli R, Del Bimbo A, Del Tongo L, Serra G (2013) Copy-move forgery detection and localization by means of robust clustering with J-linkage. Signal Process Image Commun 28:659–669Article Google Scholar Amerini I, Uricchio T, Ballan L, Caldelli R (2017) Localization of JPEG double compression through multi-domain convolutional neural networks. In: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. Work., IEEE, pp. 1865–1871Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Comput Vis Image Underst 110:346–359Article Google Scholar Bayar B, Stamm MC (2016) A deep learning approach to universal image manipulation detection using a new convolutional layer. In: Proc. 4th ACM Work. Inf. Hiding Multimed. Secur., pp. 5–10Bi X, Wei Y, Xiao B, Li W (2019) Rru-net: The ringed residual u-net for image splicing forgery detection. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit. Work., p. 0Bo X, Junwen W, Guangjie L, Yuewei D (2010) Image copy-move forgery detection based on SURF. In: 2010 Int. Conf. Multimed. Inf. Netw. Secur., IEEE, pp. 889–892Bondi L, Lameri S, Güera D, Bestagini P, Delp EJ, Tubaro S (2017) Tampering detection and localization through clustering of camera-based CNN features. In: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. Work., IEEE, pp. 1855–1864Chauhan D, Kasat D, Jain S, Thakare V (2016) Survey on keypoint based copy-move forgery detection methods on image. Procedia Comput Sci 85:206–212Article Google Scholar Chen J, Kang X, Liu Y, Wang ZJ (2015) Median filtering forensics based on convolutional neural networks. IEEE Signal Process Lett 22:1849–1853Article Google Scholar Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. IEEE Trans. Inf. Forensics Secur. 7:1841–1854Article Google Scholar Columbia Image Splicing Detection Evaluation Dataset, (n.d.) DVMM microsoft security essentials pl, microsoft essential, Microsoft Security Essentials 32-Bit, essential microsoft, microsoft security essentials 32 bit, ms essential, essential security, microsoft antywirus, microsoft security essentials, Essential Security 32-Bit Download Lippi G, Henry BM. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir Med. 2020;167:105941. PubMed PubMed Central Google Scholar Hirsch JS, Ng JH, Ross DW, Sharma P, Shah HH, Barnett RL, et al. Acute kidney injury in patients hospitalized with COVID-19. Kidney Int. 2020;98(1):209–18. CAS PubMed PubMed Central Google Scholar Moon AM, Webb GJ, Aloman C, Armstrong MJ, Cargill T, Dhanasekaran R, et al. High mortality rates for SARS-CoV-2 infection in patients with pre- existing chronic liver disease and cirrhosis: preliminary results from an international registry. J Hepatol. 2020;73(3):705–8. CAS PubMed PubMed Central Google Scholar Fadini GP, Morieri ML, Longato E, Avogaro A. Prevalence and impact of diabetes among people infected with SARS-CoV-2. J Endocrinol Investig. 2020;43(6):867–9. CAS Google Scholar Gao Y, Chen Y, Liu M, Shi S, Tian J. Impacts of immunosuppression and immunodeficiency on COVID-19: a systematic review and meta-analysis. J Inf Secur. 2020;81(2):e93–5. CAS Google Scholar Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis. 2020;94:91–5. CAS PubMed PubMed Central Google Scholar Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: a systematic literature review and meta-analysis. J Inf Secur. 2020;81(2):e16–25. CAS Google Scholar Zhang H, Han H, He T, Labbe KE, Hernandez AV, Chen H et al. Clinical Characteristics and Outcomes of COVID-19-Infected Cancer Patients: A Systematic Review and Meta-Analysis. J Natl Cancer Inst. 2020;Online ahead of print.Pranata R, Huang I, Lim MA, Wahjoepramono EJ, July J. Impact of cerebrovascular and cardiovascular diseases on mortality and severity of COVID-19-systematic review, meta-analysis, and meta- regression. J Stroke Cerebrovasc Dis. 2020;29(8):104949. PubMed PubMed Central Google Scholar Aziz F, Mandelbrot D, Singh T, Parajuli S, Garg N, Mohamed M, et al. Early report on published outcomes in kidney transplant recipients compared to nontransplant patients infected with coronavirus disease 2019. Transplant Proc. 2020;52(9):2659–62. CAS PubMed PubMed Central Google Scholar Aziz H, Lashkari N, Yoon YC, Kim J,

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1 Chapter Cancel anytime Subscribe now Buy Now Price excludes VAT (USA) Tax calculation will be finalised during checkout. Instant access to the full article PDF. Similar content being viewed by others ReferencesAmerini I, Ballan L, Caldelli R, Del Bimbo A, Serra G (2011) A sift-based forensic method for copy–move attack detection and transformation recovery. IEEE Trans. Inf. Forensics Secur. 6:1099–1110Article Google Scholar Amerini I, Ballan L, Caldelli R, Del Bimbo A, Del Tongo L, Serra G (2013) Copy-move forgery detection and localization by means of robust clustering with J-linkage. Signal Process Image Commun 28:659–669Article Google Scholar Amerini I, Uricchio T, Ballan L, Caldelli R (2017) Localization of JPEG double compression through multi-domain convolutional neural networks. In: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. Work., IEEE, pp. 1865–1871Bay H, Ess A, Tuytelaars T, Van Gool L (2008) Speeded-up robust features (SURF). Comput Vis Image Underst 110:346–359Article Google Scholar Bayar B, Stamm MC (2016) A deep learning approach to universal image manipulation detection using a new convolutional layer. In: Proc. 4th ACM Work. Inf. Hiding Multimed. Secur., pp. 5–10Bi X, Wei Y, Xiao B, Li W (2019) Rru-net: The ringed residual u-net for image splicing forgery detection. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit. Work., p. 0Bo X, Junwen W, Guangjie L, Yuewei D (2010) Image copy-move forgery detection based on SURF. In: 2010 Int. Conf. Multimed. Inf. Netw. Secur., IEEE, pp. 889–892Bondi L, Lameri S, Güera D, Bestagini P, Delp EJ, Tubaro S (2017) Tampering detection and localization through clustering of camera-based CNN features. In: 2017 IEEE Conf. Comput. Vis. Pattern Recognit. Work., IEEE, pp. 1855–1864Chauhan D, Kasat D, Jain S, Thakare V (2016) Survey on keypoint based copy-move forgery detection methods on image. Procedia Comput Sci 85:206–212Article Google Scholar Chen J, Kang X, Liu Y, Wang ZJ (2015) Median filtering forensics based on convolutional neural networks. IEEE Signal Process Lett 22:1849–1853Article Google Scholar Christlein V, Riess C, Jordan J, Riess C, Angelopoulou E (2012) An evaluation of popular copy-move forgery detection approaches. IEEE Trans. Inf. Forensics Secur. 7:1841–1854Article Google Scholar Columbia Image Splicing Detection Evaluation Dataset, (n.d.) DVMM

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Lippi G, Henry BM. Chronic obstructive pulmonary disease is associated with severe coronavirus disease 2019 (COVID-19). Respir Med. 2020;167:105941. PubMed PubMed Central Google Scholar Hirsch JS, Ng JH, Ross DW, Sharma P, Shah HH, Barnett RL, et al. Acute kidney injury in patients hospitalized with COVID-19. Kidney Int. 2020;98(1):209–18. CAS PubMed PubMed Central Google Scholar Moon AM, Webb GJ, Aloman C, Armstrong MJ, Cargill T, Dhanasekaran R, et al. High mortality rates for SARS-CoV-2 infection in patients with pre- existing chronic liver disease and cirrhosis: preliminary results from an international registry. J Hepatol. 2020;73(3):705–8. CAS PubMed PubMed Central Google Scholar Fadini GP, Morieri ML, Longato E, Avogaro A. Prevalence and impact of diabetes among people infected with SARS-CoV-2. J Endocrinol Investig. 2020;43(6):867–9. CAS Google Scholar Gao Y, Chen Y, Liu M, Shi S, Tian J. Impacts of immunosuppression and immunodeficiency on COVID-19: a systematic review and meta-analysis. J Inf Secur. 2020;81(2):e93–5. CAS Google Scholar Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: a systematic review and meta-analysis. Int J Infect Dis. 2020;94:91–5. CAS PubMed PubMed Central Google Scholar Zheng Z, Peng F, Xu B, Zhao J, Liu H, Peng J, et al. Risk factors of critical & mortal COVID-19 cases: a systematic literature review and meta-analysis. J Inf Secur. 2020;81(2):e16–25. CAS Google Scholar Zhang H, Han H, He T, Labbe KE, Hernandez AV, Chen H et al. Clinical Characteristics and Outcomes of COVID-19-Infected Cancer Patients: A Systematic Review and Meta-Analysis. J Natl Cancer Inst. 2020;Online ahead of print.Pranata R, Huang I, Lim MA, Wahjoepramono EJ, July J. Impact of cerebrovascular and cardiovascular diseases on mortality and severity of COVID-19-systematic review, meta-analysis, and meta- regression. J Stroke Cerebrovasc Dis. 2020;29(8):104949. PubMed PubMed Central Google Scholar Aziz F, Mandelbrot D, Singh T, Parajuli S, Garg N, Mohamed M, et al. Early report on published outcomes in kidney transplant recipients compared to nontransplant patients infected with coronavirus disease 2019. Transplant Proc. 2020;52(9):2659–62. CAS PubMed PubMed Central Google Scholar Aziz H, Lashkari N, Yoon YC, Kim J,

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Technol., IEEE, pp. 706–710Qureshi AM, Deriche M (2014) A review on copy-move image forgery detection techniques, multi-conference on systems. Signals & Devices (SSD):11–14Rao Y, Ni J (2016) A deep learning approach to detection of splicing and copy-move forgeries in images. In: 2016 IEEE Int. Work. Inf. Forensics Secur., IEEE, pp. 1–6Redi JA, Taktak W, Dugelay JL (2011) Digital image forensics: a booklet for beginners. Multimed Tools Appl 51:133–162Article Google Scholar Ryu S-J, Kirchner M, Lee M-J, Lee H-K (2013) Rotation invariant localization of duplicated image regions based on Zernike moments. IEEE Trans Inf Forensics Secur 8:1355–1370Article Google Scholar Salloum R, Ren Y, Kuo C-CJ (2018) Image splicing localization using a multi-task fully convolutional network (MFCN). J Vis Commun Image Represent 51:201–209Article Google Scholar Shivakumar BL, Baboo SS (2011) Detection of region duplication forgery in digital images using SURF. Int J Comput Sci Issues 8:199 Google Scholar Tralic D, Zupancic I, Grgic S, M. Grgic (2013) CoMoFoD — new database for copy-move forgery detection. Proceedings ELMAR-2013, pp. 49–54Wang X, Wang H, Niu S, Zhang J (2019) Detection and localization of image forgeries using improved mask regional convolutional neural network. Math Biosci Eng MBE 16:4581–4593Article Google Scholar Wu Y, Abd-Almageed W, Natarajan P (2018) Busternet: Detecting copy-move image forgery with source/target localization. In: Proc. Eur. Conf. Comput. Vis., pp. 168–184Yang J, Ran P, Xiao D, Tan J (2013) Digital image forgery forensics by using undecimated dyadic wavelet transform and Zernike moments. J Comput Inf Syst 9:6399–6408 Google Scholar Zhang J, Ruan Q, Jin Y (2014) Combined SIFT and bi-coherence features to detect image forgery. In: 2014 12th Int. Conf. Signal Process., IEEE, pp. 1859–1863Zhang W, Yang Z, Niu S, Wang J (2016) Detection of copy-move forgery in flat region based on feature enhancement. In: Int. Work. Digit. Watermarking, Springer, pp. 159–171Zhang Y, Goh J, Win LL, Thing VLL (2016) Image Region Forgery Detection: A Deep Learning Approach., SG-CRC. 2016, 1–11Zhao J, Guo J (2013) Passive forensics for copy-move image forgery using a method based on DCT and SVD. Forensic Sci Int 233:158–166Article Google Scholar Zheng Y, Cao Y, Chang C-H (2019) A

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