Browsing by Subject "PCA"

Now showing items 1-15 of 15

    • Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques 

      Nirjhor, S M Mahsanul Islam; Chowdhury, Mohammad Abidur Rahman; Sabab, Md. Nazmus (Brac University, 2019-08)
      In the area of machine learning, speech recognition was always a hot topic but as world's 8th most widely spoken language Bangla hasn't got the focus as much as she deserved. This research will be on speech recognition ...

    • Best feature selection and data visualization for breast cancer prediction 

      Hemel, Tanjim Ahmed; Parvez, Rohan (Brac University, 2019-09)
      Breast cancer (BC) is one of the most common cancers among women worldwide, representing the majority of new cancer cases and cancer-related deaths according to global statistics, making it a signifcant public health ...

    • Breast cancer prediction using different machine learning models 

      Khandker Al- Muhaimin; Tahsan Mahmud; Sudeepta Acharya; Ashiqul Islam (Brac University, 2019-08)
      Breast cancer is often the most lethal diseases with a large mortality rate especially among women. Despite the severe effect of the disease, it is possible to pinpoint the genre of breast cancer using diff t machine ...

    • Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN 

      Bhuiyan, Mazedul Haque; Tabassum, Fariba; Bushra, Umme; Shwon, Md.Mahbub Rahman (Brac University, 2020-04)
      Uterine cervical cancer is the second most regular gynecological harm around the world. The appraisal of the degree of sickness is fundamental for arranging ideal treatment. Imaging procedures are progressively utilized ...

    • Customer segmentation using K-means 

      Mahdee, Nafis; Shourav, Ishrak Rahman; Tabassum, Tasneem; Nur, Eman; Md Amir, Hamza Howlader (Brac University, 2022-05)
      Sales Maximization is a critical aspect of operating any business. Our thesis aims to help businesses to probe deep into their market reach as we group customers us ing the customer segmentation approach. Our dataset is ...

    • Demystifying machine learning models for IOT attack detection with explainable AI 

      Muna, Rabeya Khatun; Maliha, Homaira Tasnim; Hasan, Mahedi (Brac University, 2021-09)
      Internet of things (IoT) dramatically is changing our lives with its newly invented devices and applications which leads to various emerging cybersecurity challenges or threats. The rapid growth of IoT arouses security ...

    • Detection and prediction of epileptic seizure using different machine learning classifiers 

      Crystal, Afnan Ahmed; Tasnim, Nuna; Jamal, Subha Sumaiya B; Rahman, Md. Ashikur (Brac University, 2022-05-29)
      Analyzing neural signals produced by neurons in the brain, epilepsy can be diagnosed. An electroencephalogram (EEG) measures brain electrical activity, and studying EEG data in order to detect epileptic seizures in their ...

    • Gene expression analysis using machine learning 

      Mostafa, Nafis (Brac University, 2021-01)
      Cancer is a multifactorial disorder that occurs due to the complex interaction between the environment and gene. The susceptibility of a person to cancer depends on his genetic build-up. Recently, the study of genomes in ...

    • Handwritten character recognition and prediction of age, gender and handedness using machine learning 

      Al Emran, Md.; Naief, S. M.; Hossain, Md. Shimul (BRAC University, 2018)
      Handwritten character recognition and prediction of age, gender & handedness from handwritten documents offers an interesting research problem for researchers as few research carried out on this field. The aim of this ...

    • Hardware architecture design of face recognition system based on FPGA 

      Mondol, Raktim Kumar; Khan, Muhammadimran; Mahbubul, Hye, A. K.; Hassan, Asif S. (© 2015 Institute of Electrical and Electronics Engineers Inc., 2015)
      A novel hardware architecture for face-recognition system has been proposed in this paper. In order to make the system cost effective a simple yet efficient algorithm of face-recognition system has been used. We have ...

    • LRFS: online shoppers’ behavior based efficient customer segmentation model 

      Khan, Riyo Hayat (Brac University, 2023-02)
      The popularity of online shopping has grown significantly across the globe in recent years. This research proposes a customer segmentation model LRFS, an extended version of LRF model, built specifically for online ...

    • Night mode face recognition using adaptively weighted sub-pattern PCA 

      Alom, Md. Zahangir; Khan, Arif; Biswas, Rubel; Khan, Mumit (© 2012 IEEE, 2012)
      The face recognition problem is made difficult by the great variability in head rotation and tilt, lighting intensity and angle, facial expression, aging, partial occlusion (e.g. Wearing Hats, scarves, glasses etc.), etc. ...

    • Prediction of diabetes induced complications using different machine learning algorithms 

      Rahman, Tahsinur; Farzana, Sheikh Mastura; Khanom, Aniqa Zaida (BRAC University, 2018-08)
      Machine Learning is an ever expanding field of Artificial Intelligence which uses huge amount of data to develop algorithms that can detect patterns and systems. One such application of Machine Learning is developing ...

    • Reconstruction of images with RPCA and augmenting 3D model 

      Tahiti, Tasnia Jasim; Yusuf, Talha; Shakhawat, Chowdhury Abrar (Brac University, 2022-01)
      Crime scene photography is one of the most essential parts of documentation for all physical crime scenes in the field of forensic science. It is an organized and structured operation, having a goal of helping the ...

    • Speech emotion detection using supervised, unsupervised and feature selection algorithms 

      Rifat, Abu Nuraiya Mahfuza Yesmin; Biswas, Aditi; Chowdhury, Nadia Farhin (BRAC University, 2019-04)
      A tremendous research is being done on Speech Emotion Recognition (SER) in the recent years with its main motto to improve human machine interaction. In this thesis work,we have introduced a scheme for emotion recognition ...