• Stress Analysis in Social Media in Bengali language using BERT-based approaches 

  Khanom, Afroza; Akter, Nargis; Maisha, Sabrina Jahan; Masum, Abdul Kader M. (Scopus, 2024-12-19)

  Recent researches highlight a rapid increase in mental health issues, signaling a concerning rise in stress-related conditions such as high blood pressure, psoriasis, polycystic ovary syndrome (PCOS), etc., and these should ...
• Riot Perception and Safety Navigation of Autonomous Vehicles Using Deep Learning 

  Komol, Md. Mostafizur Rahman; Hasan, Md. Sabid; Hossain, Md. Razon; Arafat, Md. Eaysir; Arefin, Mohammad Shamsul; Rahman, Md. Mahfujur (Scopus, 2024-03-30)

  Rioting is an act of participating in a violent public disturbance, which involves multiple individuals engaging in destructive activities. Such activities can include vandalism, theft from both public and private property, ...
• Rooftop Solar Power Potential of a Municipal Area in Bangladesh 

  Hamim, Tahzib; Hossain, Md. Iqramul; Baten, Jahlak Tasmia (Scopus, 2024-04-22)

  A nation's economic growth is dependent on reliable, inexpensive energy. Bangladesh, which faces electricity shortages, intends to boost renewable energy alongside fossil fuels. Despite its small land area, the country's ...
• MobileNet-Eye: An Efficient Transfer Learning for Eye Disease Classification 

  Niloy, Golam Mohiuddin; Bitto, Abu Kowshir; Biplob, Khalid Been Md. Badruzzaman; Sammak, Musabbir Hasan; Das, Aka; Hridoy, Golam Gouse (2024-04-22)

  Precisely and promptly diagnosing eye illnesses is crucial for preventing and managing them. Transfer learning shows potential for automatically identifying different eye diseases. This is beneficial for avoiding and ...
• MN1 DN121 Vg19: A Multi-stream Ensemble Model for Detecting External Damage on Tomato Surface 

  Juthy, Most. Jebun Nahar; Tauhid; Hosen, Md. Faruk; Abul Basara, Md.; Aktar, Mst. Nargis; Shahin Uddin, Muhammad (2025-06-12)

  The use of advanced computer vision and powerful deep-learning capabilities is increasingly important in the agricultural industry, particularly for monitoring crops and detecting diseases. However, detecting external ...
• Mitigating Project Failure: Challenges in Developing Effective Building Information Modeling Execution Plans 

  Mahazir, Mashanim; Rahman, Rahimi A.; Zainudin, Nurhaizan Mohd (2024-12-29)

  The successful adoption of Building Information Modelling (BIM) relies on efficiently executing BIM Execution Plans (BEPs). Therefore, developers of BEP have to develop mitigation strategies that ensure the successful ...
• Scratch Vision Transformer Model for Diagnosis Grape Leaf Disease 

  Mamun, Sajib Bin; Ahad, Md. Taimur; Morshed, Md. Monzur; Hossain, Nafiull; Emon, Yousuf Rayhan (Scopus, 2024-06-14)

  Recently, vision transformer has gained significant attention in the field of precision agriculture for its ability to transfer knowledge from pre-trained deep models for downstream tasks, particularly with limited datasets. ...
• SEM–EDS-based rapid measurement and size-fractionated speciation of airborne particulate matter and associated metals utilizing plant leaves 

  Gajbhiye, Triratnesh; Tiwari, Ankesh; Malik, Tanzil Gaffar; Dubey, Rashmi; Pandey, Sudhir Kumar; Alharby, Hesham F.; Hakeem, Khalid Rehman (Scopus, 2024-07-10)

  This study was conducted to assess particulate matter pollution and the accumulation of airborne toxic metals by studying the foliar deposition pattern in an urban environment. To this end, two commonly growing plants ...
• Sentiment Analysis from YouTube Video Using Bi-LSTM-GRU Classification 

  Hasan, Firoz; Raza, Dewan Mamun; Moon, Hasan; Nahid, Md. Aynul Hasan (Scopus, 2024-03-30)

  Sentiment analysis is a critical area of study right now. The evolution of social media, websites, blogs, opinions, ratings, and so on. It has expanded significantly along with the development of Internet usage. Through ...
• Malicious Social Bot Detection: RL-RNN based Hybrid Approach 

  Swathi, Palagiri; Karmakar, Mousumi; Banshal, Sumit Kumar; Moni, Raka (2024-11-04)

  This paper proposes a new method called RL- RNN that combines the power of Reinforcement Learning and Recurrent Neural Networks in furthering malicious bot detection. Malicious social bots on Twitter have emerged as a ...
• Machine Vision Based Local Hyacinth Bean Breed Recognition Using Convolutional Neural Network 

  Ali Khan, Md. Abbas; Ataur Rahman, Md.; Hossain, Md Liton; Habib, Md. Tarek (2024-04-22)

  The classification is a significant one. This paper proposes a CNN-based Local Hyacinth Bean Breed Recognition (CNN-LHBR) approach along with a machine vision approach. Among the 52 breeds, we have taken only eight categories, ...
• Sentiment Analysis of Various Ride Sharing Applications Reviews: A Comparative Analysis Between Deep Learning and Machine Learning Algorithms 

  Ahammad, Md. Saymon; Sinthia, Sadia Akter; Chowdhury, Md. Muaj; Asif, Nur-A-All; Ikram, Md. Nurul Afsar (Scopus, 2024)

  The exponential growth of ride sharing platforms in developing countries has significantly transformed the landscape of urban transportation. It is crucial for service providers to comprehend customer feedback and opinions ...
• Machine Learning Models for Maternal Health Risk Prediction based on Clinical Data 

  Arman Shifa, Hasin; Uddin Mojumdar, Mayen; Md. Mohaimenur Rahman; Ranjan Chakraborty, Narayan; Gupta, Vedika (2024-04-18)

  In the healthcare industry, maternal health is of utmost importance because it directly affects the welfare of both mothers and infants. This study explores the crucial area of predicting maternal health risks with the ...
• Machine Learning for GDP Forecasting: Enhancing Economic Projections in Bangladesh 

  Ahammad, Md. Saymon; Sinthia, Sadia Akter; Hossain, Mahjabeen; Ahmed, Md. Mustak; Nurul Afsar Ikram, Md.; Nur-A-All Asif (2024-11-04)

  GDP is an important metric for measuring economic performance, directing policy decisions, simplifying investment decisions, and assessing social wellbeing. GDP prediction is important for a country’s future development. ...
• Quantitative analysis and modeling of groundwater flow using visual MODFLOW: a case from subtropical coal mine, northwest Bangladesh 

  Khan, M. Selimul Hasnian; Haque, Md. Emdadul; Ahmed, Mohd.; Islam, Abu Reza Md. Towfiqul; Fattah, Md. Abdul (Scopus, 2024-03-13)

  Despite being a vital agricultural zone and livable land for millions of people, the northwest region of Bangladesh is facing a scarcity of groundwater, which has become a major environmental stress in recent years. To ...
• Machine Learning-Based Prediction of COVID-19: A Robust Approach for Early Diagnosis and Treatment 

  Tuj Johora, Fatema; Binte Mahfuja, Israt; Masuqur Rahman, A. N. M.; Mosfikur Rahman, Md; Sadekur Rahman, Md (2024-06-14)

  The worldwide health catastrophe sparked by the COVID-19 epidemic continues, emphasizing the need for novel solutions in prediction, early diagnosis, and treatment. While vaccine development has progressed, the virus’s ...
• Machine Learning based Diagnosis of Kidney Abnormality Recognition on CT Scan Images 

  Pallab, Nafisul Mukit; Mojumdar, Mayen Uddin; Chakraborty, Narayan Ranjan; Vetrivendan, L; Akteri, Sharmin (2024-04-18)

  The healthcare industry has witnessed a surge in the adoption of machine learning due to its capacity to detect and predict diseases. The integration of machine learning and artificial intelligence (AI) is increasingly ...
• Machine Learning Approach Analysis for Early-Stage Liver Disease Prediction in the Context of Bangladesh and India 

  Sheakh, Md. Alif; Taminul Islam; Sadik, Md. Rezwane; Rana, Md. Masum (2024-02-29)

  Liver disease can cause death in millions of individuals worldwide. Early detection and accurate diagnosis improve patient outcomes and reduce mortality. Machine learning algorithms can detect and diagnose liver diseases ...
• Recurrent Neural Network Architecture to Predict Supercontinuum Generation in Chalcogenide-Silica Hybrid Photonic Crystal Fiber 

  Chowdhury, Faisal Ahmed; Rafi, Rakayet; Hasan, Md. Shahedul; Karim, M R; Rahman, B M A; Ghosh, Sampad (Scopus, 2024-12-19)

  : In this paper, we have introduced a novel deep learning approach as an efficient alternative to conventional numerical simulations for predicting supercontinuum generation in a chalcogenide-silica hybrid Photonic Crystal ...
• Real Time Flower Identification by Artificial Intelligence 

  Rahman, Moshiur; Joy, Taushik Ahmed; Abdus Sattar, Samia Akter (Scopus, 2024-03-21)

  In the realm of flower-rich Bangladesh, the presence of these blossoms enriches our everyday experiences, whether encountered during leisurely strolls, along railway tracks, or within our gardens. However, the beauty of ...

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