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A Literature Survey of Visual Similarity Snooping Attacks in Emails
(2020-08)
Snooping is one of the biggest issues that the cyber security industry is facing in this modern era of technology and it leads to big losses of finances both for individuals and organizations. The detection of snooping ...
A Suvery of Biometric Authentication Technologies Towards Secure And Robust Systems: A Case Study of Mount Kenya University
(2022-03)
In response to the increased demand for more effective authentication methods, the usage of biometric authentication to secure systems against unwanted access has grown. Because of the recent COVID-19 pandemic outbreak, ...
SSH-Brute Force Attack Detection Model based on Deep Learning
(2021-01)
The rising number of malicious threats on computer networks and Internet services owing to a large number of attacks makes the network security be at incessant risk. One of the predominant network attacks that poses ...
A Survey of Deep Learning Solutions for Anomaly Detection in Surveillance Videos
(Asian Online Journals, 2021-10)
Deep learning has proven to be a landmark computing approach to the computer vision domain. Hence, it has been widely applied to solve complex cognitive tasks like the detection of anomalies in surveillance videos. Anomaly ...
A Framework for Verification in Contactless Secure Physical Access Control and Authentication Systems
(2022-02)
Biometrics is one of the very popular techniques in user identification for accessing institutions and logging into attendance systems. Currently, some of the existing biometric techniques such as the use of fingerprints ...
Empirical Evaluation of Adaptive Optimization on the Generalization Performance of Convolutional Neural Networks
(2021-10)
Recently, deep learning based techniques have garnered significant interest and popularity in a variety of fields of research due to their effectiveness in search for an optimal solution given a finite amount of data. ...
Research Methods in Machine Learning: A Content Analysis
(2021-03)
Research methods in machine learning play a pivotal role since the accuracy and reliability of the results are influenced by the research methods used. The main aims of this paper were to explore current research methods ...
A Systematic Literature Review of Meta-Learning Models for Classification Tasks
(International Journal of Computer Applications Technology and Research Volume 11–Issue 03, 56-65, 2022)
: Meta-learning is a field of learning that aims at addressing the challenges of conventional machine learning approaches
such as learning from scratch for every new task. The main aim of this study was to do a systematic ...
Using Feature Selection Methods to Discover Common Users’ Preferences for Online Recommender Systems
(2021-01)
Recommender systems have taken over user’s choice to choose the items/services they want from online markets, where lots of merchandise is traded. Collaborative filtering-based recommender systems uses user opinions and ...
Feature Extraction using Histogram of Oriented Gradients for Image Classification in Maize Leaf Diseases
(International Journal of Computer and Information Technology, 2022)
The paper presents feature extraction methods and classification algorithms used to classify maize leaf disease images. From maize disease images, features are extracted and passed to the machine learning classification ...