A5101852099- Advanced Image and Video Retrieval Techniques
- Image Retrieval and Classification Techniques
- Metaheuristic Optimization Algorithms Research
- Video Analysis and Summarization
- Advanced Multi-Objective Optimization Algorithms
- Remote-Sensing Image Classification
- Evolutionary Algorithms and Applications
- Advanced Algorithms and Applications
- IoT and Edge/Fog Computing
- Machine Learning and ELM
- Metal complexes synthesis and properties
- Synthesis and biological activity
- Context-Aware Activity Recognition Systems
- Technology Use by Older Adults
- Synthesis and Characterization of Heterocyclic Compounds
Iqra University
2010-2021
Government of Khyber Pakhtunkhwa
2021
Shaheed Zulfiqar Ali Bhutto Institute of Science and Technology
2016
Tun Hussein Onn University of Malaysia
2012-2014
Information Technology University
2014
Particle swarm optimization (PSO) is a stochastic algorithm used for the problems proposed by Kennedy [1] in 1995. It very good technique problems. But still there drawback PSO that it stuck local minima. To improve performance of PSO, researchers different variants PSO. Some try to improving initialization swarm. them introduce new parameters like constriction coefficient and inertia weight. define method weight work on global best particles introducing mutation operators In this paper, we...
Particle Swarm Optimization (PSO) algorithm has shown good performance in many optimization problems, but PSO suffers from the problem of early convergence into a local minima. Introduction opposition based initialization and mutation operators have played an important role to overcome function optimization. In this study we reviewed different variants for Researchers proposed modifications prevent it getting stuck optima. At end, variant better conversion.
Due to the information technology which is rapidly developing, digital content becoming increasingly difficult handle. This include images that are kept on cameras, CCTV and medical scanners. Areas such as forensic science using these databases do critical tasks diagnosing of diseases or identification criminal suspects. However, manage search similar from not an easy task. Content Based Image Retrieval (CBIR) one techniques used a database. The performance CBIR depends low level (Texture,...
Particle swarm optimization (PSO) is a stochastic algorithm, used for the problems, proposed by Kennedy [1] in 1995. PSO recognized algorithm but suffers from premature convergence. This paper presents an Opposition-based (OPSO) to accelerate convergence of and at same time, avoid early The OPSO method coupled with student T mutation. Results experiment performed on standard benchmark functions show improvement performance PSO.
One of the major challenges for CBIR is to bridge gap between low level features and high semantics according need user. To overcome this gap, relevance feedback (RF) coupled with support vector machine (SVM) has been applied successfully. However, when sample small, performance SVM based RF often poor. improve RF, paper proposed a new technique, namely, PSO-SVM-RF, which combines particle swarm optimization (PSO). The aims technique are enhance also minimize user interaction system by...
Wireless Sensor Network based smart homes have the potential to meet growing challenges of independent living elderly people in homes. However, wellness detection is still a challenging research domain. Many researchers proposed several techniques; however, majority these techniques does not provide comprehensive solution because complex activities cannot be determined easily and difficult diagnose. In this study’s critical review, it has been observed that strong association lies among...
Particle Swarm is a heuristic technique based on collective behavior of birds.Several researches depicts that the PSO suffers from untimely convergence.To defeat issue convergence in several solutions are proposed to increase performance term accuracy.This paper suggests new hybrid mutation operator which used Chi-square and stable distribution.The leads swarm local minima global for better solution.To validate scheme, 12 benchmark optimization functions experiment compared result with...
Searching images from the large image databases is one of potential research areas multimedia research. The most challenging task for nay CBIR system to capture high level semantic user. researchers domain are trying fix this issue with help Relevance Feedback (RF). However existing RF based approaches needs a number iteration fulfill user's requirements. This paper proposed novel methodology achieve better results in early reduce user interaction system. In previous work it reported that...
Content Based Image Retrieval (CBIR) is an active research area in multimedia domain this era of information technology. One the challenges CBIR to bridge gap between low level features and high semantic. In study we investigate Particle Swarm Optimization (PSO), a stochastic algorithm Genetic Algorithm (GA) for overcome drawback. We proposed new system based on PSO GA coupled with Support Vector Machine (SVM). both are evolutionary algorithms used increase number relevant images. SVM...