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GENERALIZATION OF INEQUALITIES ANALOGOUS TO HERMITE–HADAMARD INEQUALITY VIA FRACTIONAL INTEGRALS
Muhammad Iqbal,Muhammad Iqbal Bhatti,Kiran Nazeer 대한수학회 2015 대한수학회보 Vol.52 No.3
Some Hermite–Hadamard type inequalities for the fractional integrals are established and these results have some relationship with the obtained results of [11, 12].
GENERALIZATION OF INEQUALITIES ANALOGOUS TO HERMITE-HADAMARD INEQUALITY VIA FRACTIONAL INTEGRALS
Iqbal, Muhammad,Iqbal Bhatti, Muhammad,Nazeer, Kiran Korean Mathematical Society 2015 대한수학회보 Vol.52 No.3
Some Hermite-Hadamard type inequalities for the fractional integrals are established and these results have some relationship with the obtained results of [11, 12].
STRONG CONVERGENCE OF NEW VISCOSITY RULES OF NONEXPANSIVE MAPPINGS
Muhammad Saeed Ahmad,Waqas Nazeer,Mobeen Munir,Sayed Fakhar Abbas Naqvi,강신민 한국전산응용수학회 2017 Journal of applied mathematics & informatics Vol.35 No.5
The aim of this paper is to present two new viscosity rules for nonexpansive mappings in Hilbert spaces. Under some assumptions, the strong convergence theorems of the purposed new viscosity rules are proved. Some applications are also included.
STRONG CONVERGENCE OF NEW VISCOSITY RULES OF NONEXPANSIVE MAPPINGS
AHMAD, MUHAMMAD SAEED,NAZEER, WAQAS,MUNIR, MOBEEN,NAQVI, SAYED FAKHAR ABBAS,KANG, SHIN MIN The Korean Society for Computational and Applied M 2017 Journal of applied mathematics & informatics Vol.35 No.5
The aim of this paper is to present two new viscosity rules for nonexpansive mappings in Hilbert spaces. Under some assumptions, the strong convergence theorems of the purposed new viscosity rules are proved. Some applications are also included.
EAR: Enhanced Augmented Reality System for Sports Entertainment Applications
( Zahid Mahmood ),( Tauseef Ali ),( Nazeer Muhammad ),( Nargis Bibi ),( Imran Shahzad ),( Shoaib Azmat ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.12
Augmented Reality (AR) overlays virtual information on real world data, such as displaying useful information on videos/images of a scene. This paper presents an Enhanced AR (EAR) system that displays useful statistical players’ information on captured images of a sports game. We focus on the situation where the input image is degraded by strong sunlight. Proposed EAR system consists of an image enhancement technique to improve the accuracy of subsequent player and face detection. The image enhancement is followed by player and face detection, face recognition, and players’ statistics display. First, an algorithm based on multi-scale retinex is proposed for image enhancement. Then, to detect players’ and faces’, we use adaptive boosting and Haar features for feature extraction and classification. The player face recognition algorithm uses boosted linear discriminant analysis to select features and nearest neighbor classifier for classification. The system can be adjusted to work in different types of sports where the input is an image and the desired output is display of information nearby the recognized players. Simulations are carried out on 2096 different images that contain players in diverse conditions. Proposed EAR system demonstrates the great potential of computer vision based approaches to develop AR applications.
Kang Shin Min,Farid Ghulam,Nazeer Waqas,Usman Muhammad 경남대학교 수학교육과 2019 Nonlinear Functional Analysis and Applications Vol.24 No.1
In this paper we have established a new identity for Katugampola fractional integrals. By using it we have found some generalizations of Riemann-Liouville fractional integral inequalities of Ostrowski type for (α,m)-convex functions. Also we prove some inequalities by taking particular appropriate values of α and m.
( Mahmood Ul Haq ),( Aamir Shahzad ),( Zahid Mahmood ),( Ayaz Ali Shah ),( Nazeer Muhammad ),( Tallha Akram ) 한국인터넷정보학회 2019 KSII Transactions on Internet and Information Syst Vol.13 No.6
Face recognition systems have several potential applications, such as security and biometric access control. Ongoing research is focused to develop a robust face recognition algorithm that can mimic the human vision system. Face pose, non-uniform illuminations, and low-resolution are main factors that influence the performance of face recognition algorithms. This paper proposes a novel method to handle the aforementioned aspects. Proposed face recognition algorithm initially uses 68 points to locate a face in the input image and later partially uses the PCA to extract mean image. Meanwhile, the AdaBoost and the LDA are used to extract face features. In final stage, classic nearest centre classifier is used for face classification. Proposed method outperforms recent state-of-the-art face recognition algorithms by producing high recognition rate and yields much lower error rate for a very challenging situation, such as when only frontal (0<sup>0</sup>) face sample is available in gallery and seven poses (0<sup>0</sup>, ±30<sup>0</sup>, ±35<sup>0</sup>, and ±45<sup>0</sup>) as a probe on the LFW and the CMU Multi-PIE databases.