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Deep Learning Based Efficient Crowd Counting System

Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed Khalid Al-Ghanem emad ul haq qazi Muhammad Hamza Faheem Syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

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Deep Learning-Based Digital Image Forgery Detection Using Transfer Learning

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Intelligent Automation & Soft Computing 2023年第12期38卷 225-240页

作者： emad ul haq qazi Tanveer Zia Muhammad Imran Muhammad Hamza Faheem Center of Excellence in Cybercrimes and Digital Forensics(CoECDF) Naif Arab University for Security Sciences(NAUSS)Riyadh14812Saudi Arabia School of Engineering Information Technology and Physical SciencesFederation UniversityBrisbaneQLD 4000Australia

Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be *** the current cyber world where deepfakes have shaken the global community,confirming the legitimacy of a digital image is of great *** the advancements made in deep learning techniques,now we can efficiently train and develop state-of-the-art digital image forensic *** most traditional and widely used method by researchers is convolution neural networks(CNN)for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for ***,in this study,a transfer learning based deep learning technique for image forgery detection is *** proposed methodology consists of three modules namely;preprocessing module,convolutional module,and the classification *** using our proposed technique,the training time is drastically reduced by utilizing the pre-trained *** performance of the proposed technique is evaluated by using benchmark datasets,i.e.,BOW and BOSSBase that detect five forensic types which include JPEG compression,contrast enhancement(CE),median filtering(MF),additive Gaussian noise,and *** evaluated the performance of our proposed technique by conducting various experiments and case scenarios and achieved an accuracy of 99.92%.The results show the superiority of the proposed system.

关键词： Image forgery transfer learning deep learning BOW dataset BOSSBase dataset

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Is economic fitness helpful in achieving environmental sustainability in BRICS economies?A risk exposure perspective

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Chinese Journal of Population,Resources and Environment 2024年第2期22卷 109-117页

作者： Jabbar ul-haq Hubert Visas Muhlis Can qazi Muhammad Adnan Hye Noreen Aslama Department of Economics University of SargodhaSargodha 40100Pakistan School of International Trade&Economics University of International Business and EconomicsBeijing 100029China Middle East University Amman 11831Jordan Vishi Higher Institute DoualaCameroon BETA Akademi Social Sciences Research Lab(SSR Lab)Istanbul 34000Turkey Academic Research and Development Wing DubaiUnited Arab Emirates

A country’s ability to create complex goods and diversify its lines of products is essential for addressing all types of *** a country’s vulnerability to extreme climatic events,such as droughts,superstorms,and other natural disasters,and its capacity for successful adaption,is an essential global need that has been *** study examines the role of economic fitness(EF)in addressing climate change risk ex‐posure in BRICS countries in the context of the environmental Kuznets curve using panel data from 1995 to *** threshold methodology is employed to ascertain the nonlinear relationship between EF and climate change risk exposure(i.e.,Notre Dame Global Adaptation Initiative Country Index(ND-GAIN)).In addition,empirical associations were estimated using panel-corrected standard errors,Driscoll-Kraay standard errors,and feasible generalized least squares estimation *** findings demonstrated an inverted N shaped link between EF and ***,even after controlling for significant ND-GAIN influencing variables such as gross domestic product per capita,financial development,and urbanization,our robustness checks revealed significant and consistent findings.

关键词： Economic fitness Climate change BRICS countries Environmental Kuznets Curve Notre Dame Index

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Trends in species distribution modelling in context of rare and endemic plants:a systematic review

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Ecological Processes 2022年第1期11卷 525-535页

作者： Ammad Waheed qazi Zafeer Saqib Muhammad Zaman‑ul‑haq Department of Environmental Science International Islamic University IslamabadIslamabad 46000Pakista

Background:Many research papers have utilized Species Distribution Models to estimate a species’current and future geographic distribution and environmental *** study aims to(a)understand critical features of SDMs used to model endemic and rare species and(b)to identify possible constraints with the collected *** present systematic review examined how SDMs are used on endemic and rare plant species to identify optimal practices for future ***:The evaluated literature(79 articles)was published between January 2010 and December *** number of papers grew considerably over *** studies were primarily conducted in Asia(41%),Europe(24%),and Africa(2%).The bulk of the research evaluated(38%)focused on theoretical ecology,climate change impacts(19%),and conservation policy and planning(22%).Most of the papers were published in publications devoted to biodiversity conservation,ecological or multidisciplinary *** degree of uncertainty was not disclosed in most studies(81%).Conclusion:This systematic review provides a broad overview of the emerging trends and gaps in the SDMs *** majority of studies failed to present uncertainties and error ***,when model performance estimates are given,the model results will be highly effective,allowing for more assurance in the predictions they ***,based on our systematic review,we recommend that in the future rare and endemic SDMs should represent uncertainty levels and estimates of errors in the modelling process.

关键词： Species distribution modelling Endemic Rare Uncertainty measures Model validation

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