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About 6,385 papers for “Cascade algorithm”
Kim, Eun-Youn, Yoon, Sung Ho · Zenodo (CERN European Organization for Nuclear Research) · 2019
Collection of MATLAP source codes for implementing cascade algorithm. For more information, please see the publication: Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks.
Cited by 0Open access
Kim, Eun-Youn, Yoon, Sung Ho · Figshare · 2019
Collection of MATLAP source codes for implementing cascade algorithm. For more information, please see the publication: Identification of critical connectors in the directed reaction-centric graphs of microbial metabolic networks.
Cited by 0Open access
Yusheng-Hu · Zenodo (CERN European Organization for Nuclear Research) · 2026
An optimized iterative algorithm for Full Permutation generation that challenges the O ( N ! ) amortized complexity barrier. Ring-Cascade-Permutation-Algorithm is a transformative generation framework for permutations that shatters the operational bottlenecks of classical combinatorial algorithms. By introducing a triple-segment memory mirroring topology, this framework demonstrates that active logic overhead can be structurally decoupled from the n ! sequence scale.
Cited by 0Open access
Yusheng-Hu · Zenodo (CERN European Organization for Nuclear Research) · 2026
An optimized iterative algorithm for Full Permutation generation that challenges the O ( N ! ) amortized complexity barrier. Ring-Cascade-Permutation-Algorithm is a transformative generation framework for permutations that shatters the operational bottlenecks of classical combinatorial algorithms. By introducing a triple-segment memory mirroring topology, this framework demonstrates that active logic overhead can be structurally decoupled from the n ! sequence scale.
Cited by 0Open access
George Emanuel · Journal of Computational Physics · 1981
Cited by 2
Noelia Vállez (5664466), Oscar Deniz (773392), Gloria Bueno (773393) · Figshare · 2015
Cited by 0Open access
M. Segal, E. Weinstein · Proceedings of the IEEE · 1988
The estimate-maximize (EM) algorithm is an iterative method for finding maximum-likelihood parameter estimates from incomplete data. The authors develop an extension of the EM algorithm that may be useful in accelerating the algorithm and in simplifying the computations involved. The extension works with an intermediate complete data specification, and performs intermediate steps at some iterations. The authors consider the problem of parameter identification of a continuous-time linear dynamic system given discrete-time observations, and show that the proposed algorithm accelerates the convergence of the EM algorithm and simplifies the computations involved.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cited by 15
Lawton Lee, S. L. Lee, Zuowei Shen · 1998
. A necessary and sufficient condition on the spectrum of the restricted transition operator is given for the convergence in L 2 (R d ) of the multidimensional cascade algorithm for any starting function OE 0 whose shifts form a partition of unity. 1. Introduction This paper is a continuation of [8]. In [8] we obtained a complete characterization of stability and orthonormality of the shifts of a refinable function in terms of its refinenent mask. In this paper we present a complete characterization of the convergence in L 2 (R d ) of the multidimensional cascade algorithm with an arbitrary dilation matrix M in terms of the mask. For fixed integers d 1 and m 2; let M be a d \\Theta d dilation matrix with j det(M)j = m: A dilation matrix is an integer matrix with all eigenvalues of modulus ? 1: Let ` 2 (Z d ); where Z d is the set of all multi-integers, be the space of all square-summable sequences, and L 2 (R d ) the space of all square-integrable functions. The...
Cited by 0
Vasavi Ravuri, Asst Prof, Somula Ramasubbareddy et al. · International Journal of Recent Technology and Engineering (IJRTE) · 2019
As one of the most successful application of Image processing, face recognition has received attention for quite a long time. Whether being used in CCTV cameras or home security, face recognition is an important application in today’s metropolitan era. The face recognization strategy is implemented by using Haar cascade algorithm. Both are used differently and the results are then compared to know which one works better or is more accurate. In this paper, we have used Python programing language, since this is only a basic Face recognition system there is no database used but for future extension, we can add a database to expand this method to a larger scale.
Cited by 2Open access
Norkhushaini Awang, Ahmad Mirza Azhar · SHILAP Revista de lepidopterología · 2025
Drowsy driving, particularly due to microsleep episodes, is a significant cause of traffic accidents, with existing solutions being often too costly or limited for widespread adoption. This project addresses this critical gap by developing a cost-effective, real-time Internet of Things (IoT)-based anti-microsleep alarm system. The system's development followed a fourstage process: Planning, Design, Development, and Evaluation. During the development phase, the system was built in Python using OpenCV and dlib for real-time facial analysis and the Haar Cascade algorithm for efficient facial feature detection. Key metrics like the Eye Aspect Ratio (EAR) and lip distance were monitored to identify signs of drowsiness and yawning. A comprehensive feedback loop was implemented using MQTT for communication between the Python backend and a Node-RED dashboard, with eSpeak and the Slack API providing aural and textual alerts. A finding from the evaluation, however, was a sensitivity to environmental factors as the distance between the driver and the camera increased, the system's accuracy in detecting drowsiness, yawning, and microsleep declined, leading to an increased risk of false negatives. Based on these results, future research should focus on enhancing the core algorithm to be more resilient to variable lighting and distance, thereby reducing false positives and negatives. Further work is also recommended to explore the system's integration with vehicle-specific infrastructure, develop more scalable data storage solutions, and conduct extensive long-term testing to validate its performance in diverse real-world driving conditions, which will pave the way for its commercial viability and broader adoption.
Cited by 0Open access
Shahad Salh Ali, Jamila Harbi Al' Ameri, Thekra Abbas · 2022
Nowadays, machines are becoming friendlier and can react to people in a faster way. Human face detection has attractive wide spread interest in recent years and become a vital factor in Human Machine Interaction and one of the most popular topics in computer vision and biometrics. The aim of this paper is to detect human face from an image containing simple and complex backgrounds using the Haar cascade algorithm. The three principal of this algorithm are: Haar-like Filter, Integral Image and the AdaBoost cascade classifier. The available Labeled Faces in the Wild (LFW) is used as the research dataset in support with OpenCV library and python programming. Our experiments show that our proposed method confirms the state-of-the-arts.
Cited by 19
Goutham N Rnsit · 2023
Cited by 0Open access
Lubo Zhou, D. Wang · 2024
Aiming at the interference problem in the electromagnetic environment of the substation site, this paper focuses on the design and optimization method of software algorithm to suppress the typical electromagnetic interference in the substation site. Focus on the feature extraction algorithm of electromagnetic interference signal, including signal preprocessing, feature extraction method and pattern recognition algorithm. On this basis, an interference suppression algorithm is designed, which combines adaptive filtering algorithm, wavelet transform algorithm and statistical analysis algorithm to realize cascade anti-interference algorithm. In order to evaluate the performance of the algorithms, a related experimental platform was built in the laboratory, and the corresponding data sets were constructed. Through experiments, the performance and effects of different algorithms were analyzed. Finally, the research results are summarized, and the further research on software algorithm design and optimization in the future is prospected.
Cited by 0
Ruilin Long, Qun Mo · Approximation Theory and Its Applications · 1999
Cited by 10
Awang, Norkhushaini, Azhar, Ahmad Mirza · UiTM Institutional Repositories (Universiti Teknologi MARA) · 2025
Drowsy driving, particularly due to microsleep episodes, is a significant cause of traffic accidents, with existing solutions being often too costly or limited for widespread adoption. This project addresses this critical gap by developing a cost-effective, real-time Internet of Things (IoT)-based anti-microsleep alarm system. The system's development followed a fourstage process: Planning, Design, Development, and Evaluation. During the development phase, the system was built in Python using OpenCV and dlib for real-time facial analysis and the Haar Cascade algorithm for efficient facial feature detection. Key metrics like the Eye Aspect Ratio (EAR) and lip distance were monitored to identify signs of drowsiness and yawning. A comprehensive feedback loop was implemented using MQTT for communication between the Python backend and a Node-RED dashboard, with eSpeak and the Slack API providing aural and textual alerts. A finding from the evaluation, however, was a sensitivity to environmental factors as the distance between the driver and the camera increased, the system's accuracy in detecting drowsiness, yawning, and microsleep declined, leading to an increased risk of false negatives. Based on these results, future research should focus on enhancing the core algorithm to be more resilient to variable lighting and distance, thereby reducing false positives and negatives. Further work is also recommended to explore the system's integration with vehicle-specific infrastructure, develop more scalable data storage solutions, and conduct extensive long-term testing to validate its performance in diverse real-world driving conditions, which will pave the way for its commercial viability and broader adoption.
Cited by 0
Braess, D., Dahmen, W., Aachen Technische Hochschule (Germany). Inst. fuer Geometrie und Praktische Mathematik · OpenGrey (Institut de l'Information Scientifique et Technique) · 1997
A variant of multigrid schemes for the Stokes problem is discussed. In particular, we propose and analyse a cascadic version for the Stokes problem. The analysis of the transfer between the grids requires special care in order to establish that the complexity is the same as that for classical multigrid algorithms. Keywords: Saddle point problems, Stokes problem, cascadic iteration, smoother, projection method 1 Introduction Multigrid methods without coarse grid corrections have been defined and applied to elliptic problems of second order by Bornemann and Deuflhard [1]. They have called it a cascadic algorithm and showed that an optimal iteration method with respect to the energy norm is obtained if conforming elements are used. Deuflhard&apos;s starting point for the cascadic multigrid method was the idea that it should be sufficient to start the iteration at the level i with a good approximation from the level i -1. A similar idea can already be found in Chapter 9 of Wachspress&apos; book...
Cited by 0
Anežka Kazíková, Krystian Łapa, Michal Pluháček et al. · Lecture notes in computer science · 2020
Cited by 1
J. Vijaya, Anurag Pratap Singh, Mary Krishna Ekka et al. · 2024
The “Face Recognition System using Python with OpenCV, Tkinter, NumPy, Image, CV2, and OS Modules” paper aims to develop an efficient and user-friendly application for facial recognition. It involves creating a personalized dataset of 200 facial images captured through a webcam using Tkinter and CV2. This dataset is crucial for training a face recognition model based on the Haar Cascade algorithm. OpenCV, Tkinter, NumPy, Image, CV2, and OS modules are leveraged to facilitate system development. Tkinter creates a user interface for easy interaction, while CV2 captures and processes facial images for dataset creation. The trained face recognition model, utilizing the Haar Cascade algorithm, is then deployed for real-time face recognition, providing instant feedback on matches. This educational and practical tool integrates Python modules for a functional facial recognition application with security, access control, and user authentication applications.
Cited by 1
Fanjun Li, Ying Li · Computer and Information Science · 2011
According to the characteristic that higher order derivatives of some base functions can be expressed by primitive functions and lower order derivatives, cascade-correlation algorithm with tunable activation functions is proposed in this paper. The base functions and its higher order derivatives are used to construct the tunable activation functions in cascade-correlation algorithm. The parallel and series constructing schemes of the activation functions are introduced. The model can simply the neural network architecture, speed up the convergence rate and improve its generalization. The efficiency is demonstrated with the two-spiral classification and Mackay-Glass time series prediction problem.
Cited by 2Open access
Yi Shen, Song Li · Applied Mathematics Letters · 2009
Cited by 2