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  • Decarbonization Blueprints for Developing Countries: The Role of Energy Productivity, Renewable Energy, and Financial Development in Environmental Improvement 
    Yan, Chen; Murshed, Muntasir; Ozturk, Ilhan; Siddik, Abu Bakkar; Ghardallou, Wafa; Khudoykulov, Khurshid (IEEE, 2023-06-15)
    As the International Energy Agency expects forecasts developing countries to become pollution hubs in the future, designing decarbonization blueprints has become critically important for the concerned governments. Hence, ...
  • Decarbonization Pathways 
    Hamid, Ishfaq; Alam, Md Shabbir; Kanwal, Asma; Jena, Pabitra Kumar; Murshed, Muntasir; Alam, Risana (Daffodil International University, 2022-02-26)
    The Paris Agreement has united the global nations to embark on pathways to the decarbonization of their respective economies. However, the objective of achieving low-carbon growth is not as straightforward as it seems since ...
  • Decarboxylation Mechanisms of the C4 Cycle in Foxtail Millet Observed Under Salt and Selenium Treatments 
    Shah, Wasifa Hafiz; Rasool, Aadil; Padder, Sajad Ahmad; Singh, Roshan Kumar; Prasad, Manoj; Tahir, Inayatullah; Rehman, Reiaz Ul; Hakeem, Khalid Rehman (Springer, 2022-08-10)
    Foxtail millet (Setaria italica L.), a millet with a smaller genome and shorter life cycle, growing in arid and semi-arid areas, is severely affected by salt stress with reduced biomass and yield. In this study, we report ...
  • Deciphering Handwritten Text: A Convolutional Neural Network Framework for Handwritten Character Recognition 
    Hossain, Md Jakir; Zaman, Sarah Samiha; Akash, Fardin Rahman; Alam, Farhana; Reza, Ahmed Wasif; Arefin, Mohammad Shamsul (Springer, 2023-11-11)
    HCR (Handwritten Character Recognition) is considered one of the most challenging research areas, given the vast array of potential applications. Character recognition has been the focus of research since the beginning of ...
  • Deciphering the Role of Quaternary N in O2 Reduction Over Controlled N-doped Carbon Catalysts 
    Haque, Enamul; Ali, Zavabeti; Uddin, Nizam; Wang, Yichao; Rahim, Md. Arifur; Syed, Nitu; Xu, Kai; Jannat, Azmira; Haque, Farjana; Zhang, Bao Yue; Shoaib, Mahbubul Alam; Shamsuddin, Sayed; Nurunnabi, Md; Harri, Andrew T.; Ou, Jian Zhen; Minett, Andrew I. (Chemistry of Materials, ACS Publications, Scopus, 2020-01-16)
    Nitrogen-doped carbon catalysts prepared from amino-functionalized metal–organic frameworks [amino-MIL-101(Al)] were investigated for the oxygen-reduction reaction (ORR) with special emphasis on elucidating the role of ...
  • A Decision Support System of Selecting Groups (Science/ Business Studies/ Humanities) for Secondary School Students in Bangladesh 
    Hasan, Rifat; Ovy, Md. Khairul Alam; Nishi, Ifrat Zahan; Hakim, Md. Azizul; Hafiz, Rubaiya (IEEE, 2020-10-15)
    As education is the only way to turn a person into human resource, every country tries to give her citizens proper scope of bringing out their inner ability by offering the appropriate education. According to the education ...
  • Deep Convolutional Comparison Architecture for Breast Cancer Binary Classification 
    Roni, Nasim Ahmed; Hossain, Md. Shazzad; Hossain, Musarrat Bintay; Efat, Md. Iftekharul Alam; Yousuf, Mohammad Abu (Springer, 2023-06-11)
    Early discernment of breast cancer can significantly improve the prospect of successful recovery and survival, but it takes a lot of time that frequently leads to pathologists disagreeing. Recently, much research has tried ...
  • A Deep Learning Approach for Bengali News Headline Categorization 
    Bandan, Sheikh Sadi; Sunve, Sabid Ahmed; Romel, Shaklian Mostak (IEEE, 2023-08-08)
    A huge amount of information and data is now available in seconds through the internet. Due to the availability of internet in the world, as the amount of online news is increasing on the one hand, people are interested ...
  • Deep Learning Approach for COVID-19 Detection: A Diagnostic Tool Based on VGG16 and VGG19 
    Akash, Fardin Rahman; Priniya, Ajmiri Afrin; Chadni, Jahani Shabnam; Shuha, Jobaida Ahmed; Emu, Ismot Ara; Reza, Ahmed Wasif; Arefin, Mohammad Shamsul (Springer, 2020-12-20)
    The coronavirus disease 2019 is a new contagious illness affecting the lungs and upper respiratory tract. It has various complications that can affect the quality of life. One of the most common factors that can be used ...
  • A Deep Learning Approach for Dengue Fever Prediction in Malaysia Using LSTM with Spatial Attention 
    Majeed, Mokhalad A.; Shafri, Helmi Zulhaidi Mohd; Zulkafli, Zed; Wayayok, Aimrun (MDPI, 2022-02-25)
    Dengue is a very common disease typically found in a widespread hot region. It is a deadly disease caused by female Aedes mosquitoes. Patients who have diagnosed with different types of dengue needed different types of ...
  • Deep Learning Approach for Detecting and Localizing Brain Tumor From Magnetic Resonance Imaging Images 
    Arefin, Abu Shahed Shah Md. Nazmul; Ishti, Shah Mohd Ishtiaque Ahammed Khan; Akter, Mst. Marium; Jahan, Nusrat (Institute of Advanced Engineering and Science (IAES), 2023-03-15)
    Brain is the most important part of the nervous system. Brain tumor is mainly a mass or growth of abnormal tissues in a brain. Early detection of brain tumor can reduce complex treatment process. Magnetic resonance images ...
  • A Deep Learning Approach to Detect and Classification of Lung Cancer 
    Khatun, Mst. Farhana; Ajmain, Moshfiqur Rahman; Assaduzzaman, Md. (IEEE, 2023-01-26)
    Cancer is a name of fear to people in the world. Ev- ery year millions of people dead of cancer in the world and lung cancer is one of them. Lung cancer is classified by our research. Non-small cell lung cancer (NSCLC) ...
  • A Deep Learning Approach to Detect Breast Cancer Disease from Mammogram Images 
    Sohel, Amir; Hossain, Shahed; Hasan, Md Umaid; Islam, Onamika; Das, Utpal Chandra; Rahman, Md. Mahfuzur (IEEE, 2023-12-15)
    Breast cancer is a significant cause of mortality among women. Breast cancer is regarded as the most severe concern among women. The early detection of breast cancer can potentially impact mortality rates significantly. ...
  • A Deep Learning Approach to Detect Microsleep Using Various Forms of EEG Signal 
    Sangeetha, S. K. B.; Mathivanan, Sandeep Kumar; Muthukumaran, V.; Pughazendi, N.; Jayagopal, Prabhu; Uddin, Md Salah (HINDAWI, 2023-02-16)
    Electroencephalography (EEG) is a reliable method for identifying the onset of sleepiness behind the wheel. Using EEG technology for driving fatigue detection still presents challenges in extracting informative elements ...
  • A Deep Learning Approach to Predict Chronic Kidney Disease in Human 
    Arafat, Faisal; Khan, Thaharim; Bapon, Atanu Das; Khan, Md. Ibrahim; Noori, Sheak Rashed Haider (Scopus, 2021)
    Renal turmoil otherwise called Chronic Kidney Disease (CKD) has been a very important field of study for a long while now. Diagnosis of CKD requires a lot of tests and it's not a straightforward or easy process. Recent ...
  • Deep Learning Approaches for Diabetic Retinopathy Detection by Image Classification 
    Bhimavarapu, Usharani; Battineni, Gopi (Daffodil International University, 2022-12-28)
    Diabetic retinopathy (DR) is among the most prevalent eye diseases that can result in blindness and vision loss if left untreated. Early detection of vision impairment might slow or stop its progression. Manual diagnosis ...
  • A Deep Learning Based Approach on Categorization of Tea Leaf 
    Kamrul, Mahadi Hasan; Rahman, Majidur; Robin, Md Risul Islam; Hossain, Md Safayet; Hasan, Mohammad Hasibul; Paul, Pritom (ACM Digital Library, 2020-01-10)
    Tea grading is a very prominent factor of the tea industry. The standard, fragrance and sweetness of tea mostly relies on this grading system. This research is a step to introduce machine learning with the tea industry, ...
  • A Deep Learning Based Assistive System to Classify COVID-19 Face Mask for Human Safety with YOLOv3 
    Bhuiyan, Md. Rafiuzzaman; Khushbu, Sharun Akter; Islam, Md. Sanzidul (IEEE, 2020-07)
    Computer vision learning pay a high attention due to global pandemic COVID-19 to enhance public health service. During the fatality, tiny object detection is a more challenging task of computer vision, as it recruits the ...
  • Deep Learning Based Classification System for Recognizing Local Spinach 
    Islam, Mirajul; Ria, Nushrat Jahan; Ani, Jannatul Ferdous; Masum, Abu Kaisar Mohammad; Abujar, Sheikh; Hossain, Syed Akhter (Springer, 2022-01-03)
    A deep learning model gives an incredible result for image processing by studying from the trained dataset. Spinach is a leaf vegetable that contains vitamins and nutrients. In our research, a Deep learning method has been ...
  • A Deep Learning Based Poisonous Frog Detection System 
    Jahan, Mushrat; Samia, Ismot Jahan; Younus, Saima Binta; Hakim, Md. Azizul; Jahan, Mushrat (IEEE, 2023-11-23)
    Frog species across the world are vulnerable and in decline, despite the fact that frogs are an integral part of biological systems. Within this enchanting world, we encounter two intriguing groups: non-poisonous and ...

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