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Browsing by Subject "Machine Learning"

Browsing by Subject "Machine Learning"

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  • Coronary Illness Prediction Using Machine Learning 
    Fairooz, Atia (Daffodil International University, 2021-01-15)
    After the advancement of the automated structure, AI expects to be a basic part here. A machine exhibit just likes a person. The system responds subsequently subject to learning. Accurate learning gives the accurate ...
  • Crime Data Mining : A General Framework and Approach to Identify Crime Pattern Using Machine Learning 
    Sharmin, Mahmuda; Kazi, Md. Aslam (Daffodil International University, 2018-11)
    Crime data mining has been a hot topic in the law-enforcement sector as it can solve crime related problems more effectively. In this thesis, we have focused in determining crime patterns using effective data mining ...
  • Crime Rate Prediction and Spot Detection System Using Machine Learning and Data Mining 
    Mahmud, Sakib; Nuha, Musfika (Daffodil International University, 2020-07-26)
    Analysis of crime is a methodological approach to the identification and assessment of criminal patterns and trends. In a number of respects cost our community profoundly. We have to go to many places every day for our ...
  • Customer Segmentation by Using Machine Learning and E-commerce Solution 
    Bepary, Anup Chandra; Ferdous, Zannatul (Daffodil International University, 2020-07-19)
    Customer segmentation is very important for online businesses like e-commerce. To grow a business a person should understand their customers very thoroughly. That’s why customer segmentation is very important. It is also ...
  • Deep Dive into Speech Privacy: Convolutional Neural Networks in Sensitive Content Detection 
    Zaman, Nafisa (Daffodil International University, 2024-01-01)
    Sensitive speech, encompassing hate speech, offensive language, and discriminatory remarks, has become a pressing issue in today's digital landscape. This research focuses on exploring the efficacy of Convolutional Neural ...
  • Deep Learning and Transfer Learning Techniques For Alzheimer's Detection From Mri Image 
    Toha, A. S. M. (Daffodil International University, 2024-01-21)
    Alzheimer's disease is a prevalent neurological condition affecting millions globally, necessitating early identification for effective management and timely intervention. Recently, deep learning techniques have emerged ...
  • Dengue Fever Prediction Using Machine Learning Approaches 
    Suchita, Ishrat (Daffodil International University, 2024-01-29)
    Dengue fever, also a viral infection spread by mosquitoes, is still a major global health concern, impacting millions of people each year. By applying a carefully controlled dataset of 521 entries and 23 variables, this ...
  • Depression prediction among student based on their daily activities 
    Pranty, Miskatun Ahmed (Daffodil International University, 2024-01-01)
    Depression affects most people in modern life. Inadequate treatment even leads to many people taking their own lives. Early detection and treatment of depression in patients are very easy to achieve. We are unable to ...
  • Determining Student's Performance Effecting Factors to Predict Their Performances Using Various Classifiers 
    Sarker, Shipankar; Roy, Limi; Akter, Farzina; Tanzeer, Arafat Ahmed (Daffodil International University, 2020-10-18)
    Student performance in university courses is of great concern to higher education where several factors may affect the performance. This paper is an attempt to apply the data mining processes, particularly classification, ...
  • Drug Addiction Prediction Using Machine Learning 
    Arif, Md. Ariful Islam; Sany, Saiful Islam; Nahin, Faiza Islam (Daffodil International University, 2020-07-19)
    Drugs and alcohol are dangerous to health and the body. Nowadays drug addiction has become a threat to Bangladeshi young people. Drugs and alcohol have a negative impact on our life. We have to keep an eye on the young ...
  • Dual Band Antenna Design and Prediction of Resonance Frequency Using Machine Learning Approaches 
    Haque, Md. Ashraful; Sarker, Nayan; Singh, Narinderjit Singh Sawaran; Rahman, Md Afzalur; Hasan, Md. Nahid; Islam, Mirajul; Zakariya, Mohd Azman; Paul, Liton Chandra; Sharker, Adiba Haque; Abro, Ghulam E. Mustafa; Hannan, Md; Pk, Ripon (Scopus, 22-10-18)
    An inset fed-microstrip patch antenna (MPA) with a partial ground structure is constructed and evaluated in this paper. This article covers how to evaluate the performance of the designed antenna by using a combination ...
  • Early Brain Stroke Prediction Using Machine Learning Technique 
    Sharmin, Toufika; Sadik, Md. Shibli (Daffodil International University, 2018-11)
    Sometimes, a stroke called a "brain attack" occurs when blood supply to an area in the brain is cut off. Often due to doctor perception, deciding whether an observation diagnostic test is brain stroke or not which causes ...
  • EEG CLASSIFICATION OF HAND MOVEMENT USING MACHINE LEARNING 
    AHMED, MD TANVIR; DAS, SOURAV; NISHA, JARIN TASNIM; GAIN, SRABANI (Daffodil International University, 2018-12-11)
    Brain computer interface can provide a communication pathway and control channel between brain and external devices. In this paper, we used global EEG dataset from UCI Machine Learning Repository (https://archive.ics.u ...
  • An Efficient Early Prediction of Hypothyroid Disease with Ensemble Machine Learning Technique 
    Nandi, Kartick (Daffodil International University, 23-02-12)
    Physical illnesses, such as hypothyroidism, have recently become more prevalent. The topic is well-known in today's society. Hypothyroidism is a problem for the majority of people. The differences between the ratios of the ...
  • An Efficient Modified Bagging Method for Early Prediction of Brain Stroke 
    Alam, Md. Mahabur; Hasan, Md. Mehadi; Hasan, Md. Zahid (Scopus, 2019-07-12)
    Brain stroke become a serious cardiovascular and cerebral disease causes of human death. Precisely predicting stroke effect from a set of predictive attributes may classify high-risk patients and guide cure approaches, ...
  • EkushNet: Using Convolutional Neural Network for Bangla Handwritten Recognition 
    Rabby, AKM Shahariar Azad; Haque, Sadeka; Abujar, Sheikh; Hossain, Syed Akhter (Elsevier B.V., 2018-11-19)
    EkushNet is the first research which can recognize Bangla handwritten basic characters, digits, modifiers, and compound characters. Handwritten recognition is one of the most interesting issue in present time due to its ...
  • An Empirical Study of Cervical Cancer Diagnosis using Ensemble Methods 
    Karim, Enamul; Neehal, Nafis (Scopus, 2019-05-05)
    Cervical Cancer, being one of the most pressing issues now-a-days, needs to be addressed properly. With a view to achieving an accurate diagnosis method for Cervical Cancer by screening the risk factors, different machine ...
  • Exploration on Use of time series analysis and machine learning to predict the population of countries and global Trend 
    Tanmoy, F.M. (Daffodil International University, 2024-01-01)
    This study focuses on the crucial task of forecasting population growth, a fundamental aspect of planning for a nation's future development. Utilizing advanced machine learning techniques, we aim to predict future ...
  • Face emotion recognition using vertically deflected and horizontally deflected face images 
    Ray, Kridita (Daffodil International University, 2024-01-24)
    Face Emotion Recognition has been a one of the common fields of work ever since Deep Leaning technology has been introduced. Although a lot of techniques have acquired a high performance, yet this technology has not been ...
  • Face Recognition for Ensuring Security in University Campus 
    Bhuiyan, Pranta Kumer; Emon, Md. Shaheed Uddin; Moon, Parves Ahmed (Daffodil International University, 2018-11)
    Face recognition is one of the most popular topics in research at present. It makes a new way in the biometrics field. It is possible for a machine to know individuals, known and unknown for this purpose called face ...

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