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RISS 인기검색어
- 검색키워드
- 저자 : Fahad Mahmood (검색결과 5 건)
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3-D Shape Recovery from Image Focus Using no-reference sharpness metric based on inherent sharpness
Fahad Mahmood,Muhammad Tariq Mahmood,Javaid Iqbal 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
Recovering an accurate depth map from its corresponding 2-D images using shape from focus architecture is a convoluted issue in computer vision and signal processing society. This paper contributes a new robust focus measure for 3-D shape recovery based on discrete wavelet transform and inherent sharpness approach. This novel focus measure technique utilizes no-reference sharpness metric based on inherent sharpness approach. The no-reference sharpness metric estimates a perceptual sharpness score based on the coefficients of discrete wavelet transform. To obtain the data of high frequency elements in an image the perceptual sharpness metric utilizes diagonal coefficients and approximated sub-signal of wavelet decomposition. The efficiency of the proposed scheme is evaluated by comparing it with state of art shape from focus approaches by conducting experiments on real and synthetic image sequences. Two global statistical metrics are utilized for performance evaluation by conducting experiments on real world images and synthetic image sequences. The evaluation is estimated on the basis of monotonicity and unimodality of the focus measure curve. The experimented results are then discussed in various forms to support the proposed scheme.
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Mahmood Khan,Muhammad Zulfaqar,Fahad Ali,Tayyab Subhani 대한금속·재료학회 2017 METALS AND MATERIALS International Vol.23 No.4
Hybrid aluminum matrix composites containing particles of boron carbide and quasicrystals were manufactured toexplore the combined effect of reinforcements on microstructural evolution and mechanical performance of thecomposites. The particles were incorporated at a loading of 6 wt% each making a total of 12 wt% reinforcement inpure aluminum. For comparison, two composites containing individually reinforced 12 wt% particles were alsoprepared along with a reference specimen of pure aluminum. Ball milling technique was employed to mix the compositeconstituents. The green bodies of composite powders were prepared by uniaxial pressing at room temperaturefollowed by consolidation by pressureless sintering under inert atmosphere. The microstructural characterizationwas performed using scanning electron microscopy while phase identification was carried out by X-ray diffraction. The mechanical characterization was performed by Vickers hardness and compression tests. Hybrid compositesshowed increased compressive properties while the composites containing solely quasicrystals demonstratedimproved hardness. The increase in mechanical performance was related to the microstructural evolution due tothe presence and uniform dispersion of binary particles.
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Unorthodox Approach to Classify EEG Signals for Upper Limb Prosthesis Application
Nasir Rashid,Fahad Mahmood,Javaid Iqbal 제어로봇시스템학회 2018 제어로봇시스템학회 국제학술대회 논문집 Vol.2018 No.10
Brain computer interface (BCI) is targeted for decoding the EEG (Electroencephalogram) signals that the human brain generates which are beneficial for the paraplegic patients. These EEG signals are slow cortical potentials that are directly recorded from scalp thus cortical neuronal activity is explored via non-invasive electrodes. These EEG signals are then further utilized for performing various operations which the paraplegic patients are unable to perform. This research article presents a novel architecture of classification of four finger movements (thumb movement, index finger movement, middle and index finger combined movement and fist movement) of the right hand on the basis of EEG (Electroencephalogram) data of the movements. The presented architecture utilizes Guided filter for reduction of noise (artefacts) from EEG signals alpha and beta band (8-30 Hz). As this band contains the maximum information of movement in terms of motor imagery. Rank Transform is employed as feature extraction approach for further enhancement of processed EEG signals. Two stage Logistic Regression classifier is finally employed for classification of movements using processed EEG signals. The experimental results demonstrate the accuracy, robustness and computational complexity of the proposed approach and have significant improvement as compared with recent architectures for EEG classification.
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Burhan Ullah,Aurangzeb Khan,Muhammad Fahad,Mahmood Alam,Allah Noor,Umar Saleem,Muhammad Kamran 한국정보처리학회 2022 Journal of information processing systems Vol.18 No.3
The capability to examine an X-ray image is so far a challenging task. In this work, we suggest a practical andnovel algorithm based on image fusion to inspect the issues such as background noise, blurriness, or sharpness,which curbs the quality of dual-energy X-ray images. The current technology exercised for the examination ofbags and baggage is “X-ray”; however, the results of the incumbent technology used show blurred and lowcontrast level images. This paper aims to improve the quality of X-ray images for a clearer vision of illegitimateor volatile substances. A dataset of 40 images was taken for the experiment, but for clarity, the results of only13 images have been shown. The results were evaluated using MSE and PSNR metrics, where the averagePSNR value of the proposed system compared to single X-ray images was increased by 19.3%, and the MSEvalue decreased by 17.3%. The results show that the proposed framework will help discern threats and theentire scanning process.
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Development and prospects of surface passivation schemes for high-efficiency c-Si solar cells
ur Rehman, Atteq,Iqbal, Muhammad Zahir,Bhopal, Muhammad Fahad,Khan, Muhammad Farooq,Hussain, Farhan,Iqbal, Javed,Khan, Mahmood,Lee, Soo Hong Elsevier 2018 Solar energy Vol.166 No.-
<P><B>Abstract</B></P> <P>Photovoltaic (PV) electric power generation has the potential to account for a major portion of power generation in the global power market. Currently, the PV market is dominated by crystalline silicon (c-Si) solar cells which accounts for more than 80% of the share. Lower cost, optimized process parameters and improved PV cell efficiencies are required to reduce the overall cost per watt peak (W). In this regard, PV cell manufacturers are currently adopting thinner wafers, which tends to increase the surface recombination velocity (SRV). Excellent surface passivation at the front and rear of the PV cell becomes imperative for realizing superior efficienciy on c-Si substrates. In this article, our focus is to discuss the role of the surface passivation process for improving the PV cell efficiency. The fundamentals and strategies to improve the surface passivation for c-Si solar cells are discussed. Surface passivation schemes and materials with the ability to offer field effect passivation with dielectric charges (positive/negative) present in the passivation films were reviewed. Moreover, we discuss the use of a thin-dielectric passivation layer with a properly selected work function and band offsets for tunneling contacts, facilitating a higher efficiency potential. Finaly, the front/rear surface passivation schemes required for thinner wafers to maintain higher bulk lifetime and higher efficiencies for c-Si solar cells are presented.</P>
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