Roundup: Synapsica scales PACS offering, ClariPi launches CT denoising solution and more briefs
Roundup: Synapsica scales PACS offering, ClariPi launches CT denoising solution and more briefs
AI radiology firm Synapsica expands PACS offering to more Indian cities
AI radiology reporting company Synapsica has partnered with GenWorks Health, a healthcare solutions provider backed by Wipro GE Healthcare, to bring its picture archiving and communication system (PACS) to more cities across India.
Its Radiolens radiology workflow solution automatically detects bad quality scans and creates…
Paper URL: https://www.ijtsrd.com/physics/engineering-physics/21727/study-on-speech-compression-and-decompression-by-using-discrete-wavelet-transform/sandar-oo
call for paper physics, physics journal, engineering journal
Speech signal can be compressed and decompressed by discrete wavelet transform technique. Discrete wavelet transform compression is based on compressing speech signal by removing redundancies present in it. Speech compression is a technique to transform speech signal into compact form. Objective of compressing speech signal is to enhance transmission and storage capacity. The compression parameters in speech such as Signal to Noise Ratio SNR , Peak Signal to Noise Ratio PSNR , Normalized Root Mean Square Error NRMSE , Compression Factor CF and Retained Signal Energy RSE are measured using Matlab.
Ich habe aus der Youtube Community (thanks to S. Pax) den freundlichen Hinweis auf die “Denoising” Funktion erhalten; diese hatte ich bislang nicht verwendet. In der Standardeinstellung werden Rauschpixel geglättet bzw. deutlich reduziert.
Abb.1 ohne Denoisung (mit Caustics, aber störende Pixel); Abb.2 mit Denoising (ziemlich optimales Ergebnis!)
Survey on Users Ranking Pattern based Trust Model Regularization in Product Recommendation
BY Sneha U | Liji Samuel" Survey on Users Ranking Pattern based Trust Model Regularization in Product Recommendation"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd11302.pdf
Direct URL: http://www.ijtsrd.com/computer-science/data-miining/11302/survey-on-users-ranking-pattern-based-trust-model-regularization-in-product-recommendation/sneha-u
indexed journal, ugc journal list, submit paper online
It is recommended to trust SVD, a trust-based matrix decomposition technique to provide advice. Trust SVD is integrated into the recommendation model to reduce data sparsity and cold start issues and their recommended performance degradation. The proposed system is a new framework for social trust data from four real-world datasets, which indicates that not only the explicit and implicit impact of ratings and trust should be considered in the recommendation model. Trust SVD extends to SVD ++, using the explicit and implicit impact of rated projects by further combining the explicit and implicit impact of trust and trust users on active user project predictions. Trust SVD to achieve better accuracy than other recommended technology methods. This method is overcome by introducing a frequency-based algorithm to reduce the error rate and avoid language problems, thereby improving the accuracy of the recommendation.
Data Processing Through Image Processing using Gaussian Minimum Shift Keying
by Nadiya Mehraj | Harveen Kour "Data Processing Through Image Processing using Gaussian Minimum Shift Keying"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18819.pdf
Direct Link: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18819/data-processing-through-image-processing-using-gaussian-minimum-shift-keying/nadiya-mehraj
open access journal of engineering, engineering journal, paper publication for engineering
Image Denoising is an important pre-processing task which is used before further processing of image. The purpose of denoising is to remove the noise while retaining the edges and other detailed features. This noise gets introduced during the process of acquisition, transmission and reception and storage and retrieval of the data. Due to this there is degradation in visual quality of image. Wavelets play a major role in image compression and image denoising as they support the property of sparsity and multi resolution structure. Wavelet Thresholding is important technique in wavelet domain filtering. Many image filters are found which perform well when the noise conditions are low. But as the noise conditions go on increasing their performance gets degraded. Thus, it is felt that there is sufficient scope to investigate and develop quite efficient but simple algorithms to suppress moderate and high power noise in images.
by Sehba Yousuf | Er. Arushi Baradwaj "Image Filtering Based on GMSK"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18403.pdf
Direct Link: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18403/image-filtering-based-on-gmsk/sehba-yousuf
open access journal of engineering, engineering journal, paper publication for engineering
Image Denoising is an important pre-processing task which is used before further processing of image. The purpose of denoising is to remove the noise while retaining the edges and other detailed features. This noise gets introduced during the process of acquisition, transmission and reception and storage and retrieval of the data. Due to this there is degradation in visual quality of image. The noises which are of major considerations are Additive White Gaussian Noise AWGN and Impulsive Noise.
