Matlab vs. OpenCV: A Comparative Study of Different Machine Learning Algorithms

Elsayed, Ahmed Ali; Yousef, Waleed A.

doi:10.48550/arxiv.1905.01213

Cited by 2 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First, the majority of the code written for this project was in Matlab; and some codes were written in C++ for computation speedup (we reported the performance comparison between Matlab and OpenCV in [134] using 20 different datasets than the dataset of our present project). At the time of this work, MATLAB did not have the currently available OpenCL toolbox.…”

Section: Gpu Implementation and Computational Acceleration For Algori...mentioning

confidence: 99%

Method and System for Image Analysis to Detect Cancer

Yousef,

Abouelkahire,

Almahallawi

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Breast cancer is the most common cancer and is the leading cause of cancer death among women worldwide. Detection of breast cancer, while it is still small and confined to the breast, provides the best chance of effective treatment. Computer Aided Detection (CAD) systems that detect cancer from mammograms will help in reducing the human errors that lead to missing breast carcinoma. Literature is rich of scientific papers for methods of CAD design, yet with no complete system architecture to deploy those methods. On the other hand, commercial CADs are developed and deployed only to vendors' mammography machines with no availability to public access. This paper presents a complete CAD; it is complete since it combines, on a hand, the rigor of algorithm design and assessment (method), and, on the other hand, the implementation and deployment of a system architecture for public accessibility (system). ( 1) We develop a novel algorithm for image enhancement so that mammograms acquired from any digital mammography machine look qualitatively of the same clarity to radiologists' inspection; and is quantitatively standardized for the detection algorithms. (2) We develop novel algorithms for masses and microcalcifications detection with accuracy superior to both literature results and the majority of approved commercial systems. (3) We design, implement, and deploy a system architecture that is computationally effective to allow for deploying these algorithms to cloud for public access.

show abstract

Section: Gpu Implementation and Computational Acceleration For Algori...mentioning

confidence: 99%

Method and System for Image Analysis to Detect Cancer

Yousef,

Abouelkahire,

Almahallawi

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Matlab and opencv too provide support for ML development. A comparison of Matlab and opencv was conducted by Ahmed and Waleed [12]. Each of the libraries and packages are usually targeted to certain types of applications and they differ in the computing resources they utilise for computation like the Mxnet for heterogeneous distributed systems, R for predictive modelling and NLTK for language processing [13] [14] [15].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning to Optimize TCP Communications Over High Frequency Communications Links

et al. 2022

View full text Add to dashboard Cite

High Frequency communication is a proven method of beyond line of sight (BLOS) communications for decades. With the advent of Wideband HF (WBHF), the ability to communicate data and more specifically TCP over HF is being researched worldwide. HF-TCP, an optimised TCP for HF links provides improved TCP communication over challenging High Frequency (HF) communication systems. It relies on the modification of Forced Retransmission Timeout (fRTO) and Mean Segment Size (MSS) to improve the reliability of communication sessions. Calculating the fRTO for a communication session that would provide the optimum result over a communication link is a complex task due to the timers that manage the session and the HF channel characteristics. In this paper, we propose the use of Machine Learning (ML) techniques to dynamically predict fRTO and MSS to improve the fRTO calculation process for all communication instances. To achieve this, a Predictor Model is used to predict fRTO and MSS while an Optimiser model optimises the Predictor model's output. Decision Tree Regression was proven to be the most accurate among the various ML algorithms tested with 82 percent prediction accuracy. The performance of HF-TCP with proposed predicted fRTO and MSS is compared with that of standard TCP and the performance of the Predictor and Optimiser models is also analysed. The results show 72 percent of instances have an improvement in link efficiency when using HF-TCP with predicted fRTO and MSS over standard TCP.

show abstract

Matlab vs. OpenCV: A Comparative Study of Different Machine Learning Algorithms

Cited by 2 publications

References 1 publication

Method and System for Image Analysis to Detect Cancer

Method and System for Image Analysis to Detect Cancer

Machine Learning to Optimize TCP Communications Over High Frequency Communications Links

Contact Info

Product

Resources

About