Loading [MathJax]/extensions/MathZoom.js
Usama Arshad - IEEE Xplore Author Profile
Subscribe
ADVANCED SEARCH

Author details

< Back

Usama Arshad

Publications
30
Citations
255
Publications by Year
20202024
Co-Authors:
Show All Co-Authors (67)
Image of author Usama Arshad

Usama Arshad

Affiliation

Faculty of Computer Science & Engg.
GIK Institute of Engg. Sciences & Tech.
Topi, Khyber Pakhtunkhwa, Pakistan

Publication Topics

Biography

Usama Arshad is currently working toward the Ph.D. degree in computer science with the Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakhtunkhwa, Pakistan.,He is working on the integration of fuzzy systems with Machine Learning and other technologies to enhance system optimization in terms of scalability, cost-effectiveness, security, privacy, and robustness.(Based on document published on 30 August 2024).
Publications
30
Citations
255
Publications by Year
20202024
Co-Authors:
Show All Co-Authors (67)
Author's Published Works

Showing 1-25 of 30 results

  • Sort

Filter Results

Show

Sort By

Results

Mitigating Adversarial and Data Poisoning Attacks in Cybersecurity Applications

Saad Rustam;Usama Arshad;Muhammad Ahmad;Najam Sawera;Hammad Ali

2024 19th International Conference on Emerging Technologies (ICET)
Year: 2024 | Conference Paper |
The integration of deep learning models in cybersecurity applications, such as malware detection, intrusion detection, and spam filtering, has introduced significant vulner-abilities to security threats. Among these, adversarial and data poisoning attacks pose particularly severe risks, compromising the reliability and accuracy of learning algorithms. Adversarial attacks involve the manipulation o...Show More

Mitigating Adversarial and Data Poisoning Attacks in Cybersecurity Applications

Saad Rustam;Usama Arshad;Muhammad Ahmad;Najam Sawera;Hammad Ali

Year: 2024 | Conference Paper |

VigilantAI: Real-time detection of anomalous activity from a video stream using deep learning

Danish Javed;Usama Arshad;Shuhrabeel Peerzada;Muhammad Ramiz Saud;Nisar Ali;Raja Hashim Ali

2024 International Conference on IT and Industrial Technologies (ICIT)
Year: 2024 | Conference Paper |
In an era where artificial intelligence (AI) solutions are increasingly integrated into various sectors, we have utilized Artificial Intelligence for enhancing public safety through real-time detection of illegal activities such as robberies and threats at gunpoint using CCTV footage. With the proliferation of deep learning in object detection, the study focuses on deploying the YoloV5 model, trai...Show More

VigilantAI: Real-time detection of anomalous activity from a video stream using deep learning

Danish Javed;Usama Arshad;Shuhrabeel Peerzada;Muhammad Ramiz Saud;Nisar Ali;Raja Hashim Ali

Year: 2024 | Conference Paper |

Genetic ledger – pioneering secure and authentic data storage through DNA and blockchain

Usama Arshad;Munam Ali Shah

International Conference on AI and the Digital Economy (CADE 2024)
Year: 2024 | Conference Paper |
The rapid increase in digital data necessitates advanced storage solutions. This paper introduces the DNA-chain system, an innovative integration of DNA data storage and blockchain technology. Our hybrid system utilizes the high-density storage capability of synthetic DNA to handle massive amounts of data, alongside blockchain’s robust security and traceability features. We detail techniques for e...Show More

Genetic ledger – pioneering secure and authentic data storage through DNA and blockchain

Usama Arshad;Munam Ali Shah

Year: 2024 | Volume: 2024 | Conference Paper |

Context-Aware Audio-Visual Speech Enhancement Based on Neuro-Fuzzy Modeling and User Preference Learning

Song Chen;Jasper Kirton-Wingate;Faiyaz Doctor;Usama Arshad;Kia Dashtipour;Mandar Gogate;Zahid Halim;Ahmed Al-Dubai;Tughrul Arslan;Amir Hussain

IEEE Transactions on Fuzzy Systems
Year: 2024 | Volume: 32, Issue: 10 | Journal Article |
It is estimated that by 2050 approximately one in ten individuals globally will experience disabling hearing impairment. In the presence of everyday reverberant noise, a substantial proportion of individual users encounter challenges in speech comprehension. This study introduces a novel application of neuro-fuzzy modeling that synergizes and fuses audio-visual speech enhancement (AV SE) with an i...Show More

Context-Aware Audio-Visual Speech Enhancement Based on Neuro-Fuzzy Modeling and User Preference Learning

Song Chen;Jasper Kirton-Wingate;Faiyaz Doctor;Usama Arshad;Kia Dashtipour;Mandar Gogate;Zahid Halim;Ahmed Al-Dubai;Tughrul Arslan;Amir Hussain

Year: 2024 | Volume: 32, Issue: 10 | Journal Article |

Influencing Factors in Facial Recognition and Verification: A Siamese Neural Network Hyperparameter Study

Ahmad Maaz;Usama Arshad;Tafreed Ahmad;Shaheer Abbas

2024 International Conference on Engineering & Computing Technologies (ICECT)
Year: 2024 | Conference Paper |
Cited by: Papers (2)
There are many practical uses for facial verification and recognition jobs. In this study, we look into the developments and difficulties faced in facial recognition technologies, especially in the application of Siamese neural networks. This study converges around optimizing hyperparameters to improve Siamese network accuracy and performance. We evaluated the impact of different optimizers, loss ...Show More

Influencing Factors in Facial Recognition and Verification: A Siamese Neural Network Hyperparameter Study

Ahmad Maaz;Usama Arshad;Tafreed Ahmad;Shaheer Abbas

Year: 2024 | Conference Paper |

Incentivizing Recycling Behavior: Repro - A Reward Based CNN-Enabled Framework for Smart Waste Collection

Haider Irfan;Usama Arshad;Hammad Anwer

2024 International Conference on Engineering & Computing Technologies (ICECT)
Year: 2024 | Conference Paper |
Efficient waste management together with certain measures to promote the recycling process are essential for over-coming global environmental issues. In this study, we describe Repro an app, which is targeted at transforming how we collect waste and recycle by integrating CNN technology and a reward-based system. Users, with the Repro app, take pictures of any trash they discard and rely on the un...Show More

Incentivizing Recycling Behavior: Repro - A Reward Based CNN-Enabled Framework for Smart Waste Collection

Haider Irfan;Usama Arshad;Hammad Anwer

Year: 2024 | Conference Paper |

Harnessing Long Short Term Memory Networks for Stock Market Forecasts

Alishba Faheem;Usama Arshad

2024 International Conference on Engineering & Computing Technologies (ICECT)
Year: 2024 | Conference Paper |
Stock market trend prediction is a classical re-gression problem with effects on stock exchange. This research is presenting a detailed exploration of how Long Short Term Memory (LSTM) networks may be used for predicting stock market trends. The LSTM model was employed instead of the conventional Recurrent Neural Networks (RNNs), to learn from historical financial data. The study examines the oper...Show More

Harnessing Long Short Term Memory Networks for Stock Market Forecasts

Alishba Faheem;Usama Arshad

Year: 2024 | Conference Paper |

Futuristic Decentralized Vehicular Network Architecture and Repairing Management System on Blockchain

Usama Arshad;Zahid Halim;Hisham Alasmary;Muhammad Waqas

IEEE Internet of Things Journal
Year: 2024 | Volume: 11, Issue: 13 | Journal Article |
Cited by: Papers (1)
Blockchain technology is used often as a merger with other technologies to achieve a high level of security, privacy, and robustness and to handle issues, such as maliciousness of nodes, privacy leakage, the selfishness of nodes, communication delays, and high execution and transaction costs. There is currently a lack of a comprehensive system for automating and cost-effectively managing vehicle r...Show More

Futuristic Decentralized Vehicular Network Architecture and Repairing Management System on Blockchain

Usama Arshad;Zahid Halim;Hisham Alasmary;Muhammad Waqas

Year: 2024 | Volume: 11, Issue: 13 | Journal Article |

Leveraging AI and NLP in Chatbot Development: An Experimental Study

Abdul Wahab Paracha;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

2023 International Conference on Frontiers of Information Technology (FIT)
Year: 2023 | Conference Paper |
Cited by: Papers (7)
In the current era of chatbots, this research delves into the advancements in AI chatbots, drawing on artificial intelligence (AI) and natural language processing (NLP) techniques to mimic human-like conversations. A particular focus is given to the potential of chatbots in facilitating multitasking dialogues, offering emotional support, and addressing complex subject matter, all the while respect...Show More

Leveraging AI and NLP in Chatbot Development: An Experimental Study

Abdul Wahab Paracha;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

Year: 2023 | Conference Paper |

Mitigating Crop Losses: AI-enabled Disease Detection in Tomato Plants

Hassan Ashfaq;Usama Arshad;Raja Hashim Ali;Zain ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

2023 International Conference on Frontiers of Information Technology (FIT)
Year: 2023 | Conference Paper |
Cited by: Papers (13)
Fostering crop health is vital for global food security, underscoring the need for effective disease detection. This research introduces an innovative artificial intelligence (AI) model designed to enhance the detection and diagnosis of diseases in tomato plants, particularly focusing on Early Blight and Late Blight. Significantly, our model leverages cutting-edge image processing techniques to im...Show More

Mitigating Crop Losses: AI-enabled Disease Detection in Tomato Plants

Hassan Ashfaq;Usama Arshad;Raja Hashim Ali;Zain ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

Year: 2023 | Conference Paper |

Robust and Reliable Liveness Detection Models for Facial Recognition Systems

Haris Anjum;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Abu Bakar Siddique;Muhammad Imad

2023 International Conference on Frontiers of Information Technology (FIT)
Year: 2023 | Conference Paper |
Cited by: Papers (8)
Facial Liveness Detection is instrumental in combating fraudulent practices and identity theft by differentiating genuine faces from forgeries. Given that facial recognition is now an integral part of many sectors like banking and law enforcement, liveness detection has become a vital aspect for maintaining the trustworthiness of these applications. Unfortunately, the utility of prevalent facial l...Show More

Robust and Reliable Liveness Detection Models for Facial Recognition Systems

Haris Anjum;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Abu Bakar Siddique;Muhammad Imad

Year: 2023 | Conference Paper |

Exploiting Partial Observability and Optimized Simple State Representations in Deep Q-Learning

Danyaal Mahmood;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

2023 International Conference on Frontiers of Information Technology (FIT)
Year: 2023 | Conference Paper |
Cited by: Papers (4)
The advent of deep Q-learning has opened up new possibilities in training autonomous agents to perform intelligently in intricate settings. This research work examines the potential of deep Q-learning in the paradigmatic Snake game, which requires an agent to navigate a grid, ingest food items, and avoid collisions. We incorporated a partially observable game state, introducing a novel level of di...Show More

Exploiting Partial Observability and Optimized Simple State Representations in Deep Q-Learning

Danyaal Mahmood;Usama Arshad;Raja Hashim Ali;Zain Ul Abideen;Muhammad Huzaifa Shah;Talha Ali Khan;Ali Zeeshan Ijaz;Nisar Ali;Abu Bakar Siddique

Year: 2023 | Conference Paper |

Performance Evaluation of Popular Deep Neural Networks for Neural Machine Translation

Muhammad Naeem;Abu Bakar Siddique;Raja Hashim Ali;Usama Arshad;Zain ul Abideen;Talha Ali Khan;Muhammad Huzaifa Shah;Ali Zeeshan Ijaz;Nisar Ali

2023 International Conference on Frontiers of Information Technology (FIT)
Year: 2023 | Conference Paper |
Cited by: Papers (10)
The field of Neural Machine Translation (NMT) has shown impressive performance for quick and easy communication in various languages spoken all over the world. NMT helps us by improving communication between different languages. For this purpose, different sequential models are used such as Recurrent Neural Network (RNN), Long Short Term Memory (LSTM), and Gated Recurrent Units (GRU). Analysis amo...Show More

Performance Evaluation of Popular Deep Neural Networks for Neural Machine Translation

Muhammad Naeem;Abu Bakar Siddique;Raja Hashim Ali;Usama Arshad;Zain ul Abideen;Talha Ali Khan;Muhammad Huzaifa Shah;Ali Zeeshan Ijaz;Nisar Ali

Year: 2023 | Conference Paper |

A New Rhythm in A1: Convolutional Neural Networks for Music Genre Classification

Huzaifa Javed;Usama Arshad;Zain ul Abideen;Raja Hashim Ali

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (14)
Despite the significance of music genre classification in audio identification, it remains under-explored within AI research. This tool is crucial for personalized music recommendations and similar music detection. We have developed an efficient AI model that leverages Convolutional Neural Networks (CNNs), offering high-precision genre identification when integrated into a graphical user interface...Show More

A New Rhythm in A1: Convolutional Neural Networks for Music Genre Classification

Huzaifa Javed;Usama Arshad;Zain ul Abideen;Raja Hashim Ali

Year: 2023 | Conference Paper |

Identifying COVID-19 through X-ray and CT scan images using Machine Learning

Maham Shehzadi;Usama Arshad;Zainul Abideen;Raja Hashim Ali;Ammad Aslam Khan;Ali Zeeshan Ijaz

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (13)
In the current global scenario, marked by the COVID-19 pandemic, it has become imperative for healthcare systems around the globe to swiftly and accurately diagnose the disease. This is where cutting-edge approaches such as machine learning (ML) come into play, specifically, ML-based identification of COVID-19 from chest X-ray and CT-Scan imagery. Our research collective is devotedly working towar...Show More

Identifying COVID-19 through X-ray and CT scan images using Machine Learning

Maham Shehzadi;Usama Arshad;Zainul Abideen;Raja Hashim Ali;Ammad Aslam Khan;Ali Zeeshan Ijaz

Year: 2023 | Conference Paper |

AdaptiveCloset: Reinforcement Learning in Personalized Clothing Recommendations

Omar Kashif Majeed;Zain ul Abideen;Usama Arshad;Raja Hashim Ali;Abdullah Habib;Rafay Mustafa

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (14)
The fashion industry, with its myriad choices, often overwhelms consumers. Addressing this, AdaptiveCloset introduces a groundbreaking approach to tailoring clothing suggestions by harnessing the power of reinforcement learning (RL). Unlike conventional AI methodologies in a fashion that merely suggests based on past preferences, our system dynamically ad-justs using realtime user feedback, ensuri...Show More

AdaptiveCloset: Reinforcement Learning in Personalized Clothing Recommendations

Omar Kashif Majeed;Zain ul Abideen;Usama Arshad;Raja Hashim Ali;Abdullah Habib;Rafay Mustafa

Year: 2023 | Conference Paper |

Innovative Poverty Estimation through Machine Learning Approaches

Ahmad Mashhood;Zain ul Abideen;Usama Arshad;Raja Hashim Ali;Ammad Aslam Khan;Bahram Khan

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (14)
This paper delves into the application and capabilities of machine learning methodologies in forecasting poverty scenarios, underlining the importance of varied data sources, along with the interpretability and explainability of models to refine the precision and transparency of poverty prediction mechanisms. It primarily utilizes an iteration of the LightGBM algorithm to infer poverty stages prem...Show More

Innovative Poverty Estimation through Machine Learning Approaches

Ahmad Mashhood;Zain ul Abideen;Usama Arshad;Raja Hashim Ali;Ammad Aslam Khan;Bahram Khan

Year: 2023 | Conference Paper |

An Enhanced Genetic Algorithm Framework for Efficient Solutions to Capacitated Vehicle Routing Problems

Usama Arshad;Hamza Hasan Ellahie;Zain ul Abideen;Raja Hashim Ali

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (15)
Capacitated Vehicle Routing Problems (CVRPs), a widely acknowledged NP-hard issue, pertains to the optimal routing of a limited-capacity vehicle fleet to fulfill customer demand, aiming for the least possible travel distance or cost. Despite the presence of numerous heuristic and exact approaches, the combinatorial characteristic of CVRP renders it challenging, especially for large-scale instances...Show More

An Enhanced Genetic Algorithm Framework for Efficient Solutions to Capacitated Vehicle Routing Problems

Usama Arshad;Hamza Hasan Ellahie;Zain ul Abideen;Raja Hashim Ali

Year: 2023 | Conference Paper |

Revolutionizing Campus Exploration with GikiLenS: A Deep Learning-Powered Object Detection App

Iqra Mueed;Usama Arshad;Raja Hashim Ali

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (14)
For newcomers and tourists, navigating university campuses can be difficult, resulting in aggravation and lost time. We respond by introducing “GikiLenS”, an object identification application driven by deep learning that revolutionizes campus exploration by accurately identifying buildings and landmarks while enhancing user experience. GikiLenS is a comprehensive and user-friendly smartphone appli...Show More

Revolutionizing Campus Exploration with GikiLenS: A Deep Learning-Powered Object Detection App

Iqra Mueed;Usama Arshad;Raja Hashim Ali

Year: 2023 | Conference Paper |

Deciphering Faces: Enhancing Emotion Detection with Machine Learning Techniques

Muhammad Haseeb Ishaq;Rafay Mustafa;Usama Arshad;Zain ul Abideen;Raja Hashim Ali;Abdullah Habib

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (13)
Facial emotion detection holds significant relevance across various domains, from psychology and marketing to education and security. Despite its importance, prevalent techniques often grapple with issues like low precision, susceptibility to lighting changes, obstructions, and distinct facial characteristics. Addressing these challenges, our research embarked on devising a robust and precise faci...Show More

Deciphering Faces: Enhancing Emotion Detection with Machine Learning Techniques

Muhammad Haseeb Ishaq;Rafay Mustafa;Usama Arshad;Zain ul Abideen;Raja Hashim Ali;Abdullah Habib

Year: 2023 | Conference Paper |

The YOLOv8 Edge: Harnessing Custom Datasets for Superior Real-Time Detection

Tafreed Ahmed;Ahmad Maaz;Danyaal Mahmood;Zain ul Abideen;Usama Arshad;Raja Hashim Ali

2023 18th International Conference on Emerging Technologies (ICET)
Year: 2023 | Conference Paper |
Cited by: Papers (14)
YOLO has become a central real-time object detection system for robotics, driverless cars, and video monitoring applications. Developing a custom object detection solution that can detect specific objects in real-time video streams has the potential to revolutionize various fields and has been the subject of extensive research. Although there have been advances in object detection, there is still ...Show More

The YOLOv8 Edge: Harnessing Custom Datasets for Superior Real-Time Detection

Tafreed Ahmed;Ahmad Maaz;Danyaal Mahmood;Zain ul Abideen;Usama Arshad;Raja Hashim Ali

Year: 2023 | Conference Paper |

Investigating novel machine learning based intrusion detection models for NSL-KDD data sets

Muhammad Huzaifa Shah;Muhammad Abu Bakar;Raja Hashim Ali;Zain Ul Abideen;Usama Arshad;Ali Zeeshan Ijaz;Nisar Ali;Muhammad Imad;Said Nabi

2023 International Conference on IT and Industrial Technologies (ICIT)
Year: 2023 | Conference Paper |
Cited by: Papers (11)
This study investigates the application of the Mutual Information (MI) feature selection technique to improve the accuracy of Machine Learning (ML) models on NSL-KDD datasets, building upon prior research. Six ML models, namely Decision Tree (DT), Logistic Regression (LR), K-Nearest Neighbor (KNN), Random Forest (RF), Naive Bayes (NB), and Support Vector Machine (SVM) with different kernels (1st, ...Show More

Investigating novel machine learning based intrusion detection models for NSL-KDD data sets

Muhammad Huzaifa Shah;Muhammad Abu Bakar;Raja Hashim Ali;Zain Ul Abideen;Usama Arshad;Ali Zeeshan Ijaz;Nisar Ali;Muhammad Imad;Said Nabi

Year: 2023 | Conference Paper |

Exploring The Potential of HMMs in Linguistics for Part of Speech (POS) Tagging

Mahnoor Iftikhar;Raja Hashim Ali;Memoona Saleem;Usama Arshad;Ali Zeeshan Ijaz;Nisar Ali;Muhammad Imad;Muhammad Abu Bakar;Ali Aftab

2023 International Conference on IT and Industrial Technologies (ICIT)
Year: 2023 | Conference Paper |
Cited by: Papers (13)
The exponential growth in the adoption of information and communication technologies has sparked a notable surge in the demand for Natural Language Processing (NLP) tools. The tagging/identification of Part-of-Speech (POS) is of utmost importance in numerous natural language processing applications, including information extraction, parsing, and machine translation. It entails the assignment of a ...Show More

Exploring The Potential of HMMs in Linguistics for Part of Speech (POS) Tagging

Mahnoor Iftikhar;Raja Hashim Ali;Memoona Saleem;Usama Arshad;Ali Zeeshan Ijaz;Nisar Ali;Muhammad Imad;Muhammad Abu Bakar;Ali Aftab

Year: 2023 | Conference Paper |

Prediction of Polycystic Ovary Syndrome Using Genetic Algorithm-driven Feature Selection

Fatima Faridoon;Raja Hashim Ali;Zain Ul Abideen;Nazia Shahzadi;Ali Zeeshan Ijaz;Usama Arshad;Nisar Ali;Muhammad Imad;Said Nabi

2023 International Conference on IT and Industrial Technologies (ICIT)
Year: 2023 | Conference Paper |
Cited by: Papers (11)
PolyCystic Ovary Syndrome (PCOS) is a hormonal disorder frequently found in women of reproductive age having a significant impact on the cause of infertility. It is an endocrine condition characterized by abnormalities in female hormone levels and aberrant synthesis of male hormones. This syndrome causes ovarian malfunction, increasing the risk of miscarriage and infertility. PCOS has a wide range...Show More

Prediction of Polycystic Ovary Syndrome Using Genetic Algorithm-driven Feature Selection

Fatima Faridoon;Raja Hashim Ali;Zain Ul Abideen;Nazia Shahzadi;Ali Zeeshan Ijaz;Usama Arshad;Nisar Ali;Muhammad Imad;Said Nabi

Year: 2023 | Conference Paper |

Performance comparison of genetic algorithms with traditional search techniques on the N-Queen Problem

Omar Kashif Majeed;Raja Hashim Ali;Ali Zeeshan Ijaz;Nisar Ali;Usama Arshad;Muhammad Imad;Said Nabi;Javaria Tahir;Memoona Saleem

2023 International Conference on IT and Industrial Technologies (ICIT)
Year: 2023 | Conference Paper |
Cited by: Papers (6)
This paper presents an analysis of solving the N-Queen problem using a genetic algorithm and compares its performance with traditional search algorithms like breadth-first search (BFS) and depth-first search (DFS). The N-Queen problem is a famous problem in the field of artificial intelligence that has been studied in depth. The genetic algorithm is an optimization algorithm inspired by the proces...Show More

Performance comparison of genetic algorithms with traditional search techniques on the N-Queen Problem

Omar Kashif Majeed;Raja Hashim Ali;Ali Zeeshan Ijaz;Nisar Ali;Usama Arshad;Muhammad Imad;Said Nabi;Javaria Tahir;Memoona Saleem

Year: 2023 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.