Browsing by Subject "Feature extraction"

Now showing items 1-15 of 15

    • Automatic motor vehicle number plate recognition 

      Saha, Krishno; Ishrak, Parvez; Shovon, Jahid Hossian; Abir, Alinur Rahman (Brac University, 2024-01)
      The purpose of this initiative is to develop automatic motor vehicle number plate recognition (Bangla) using machine learning, identifying and taking out the numbers of license plates from photos. By using this system ...

    • Clustering and detection of good and bad rail line anchors from images 

      Islam, Samiul; Khan, Rubayat Ahmed (© 2015 Institute of Electrical and Electronics Engineers Inc., 2016-06)
      Absence of railway anchors/fasteners is a serious concern as it might lead to severe consequences such as train derailments. Hence regular inspection is an obligation to ensure safety. The third world countries choose the ...

    • 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 ...

    • DWT based transformed domain feature extraction approach for epileptic seizure detection 

      Mostafa, Mahajabin; Samin, Mohtasim Abrar; Hassan, Nabila Bintey; Nibras, Saiara Zerin; Rahman, Samir (Brac University, 2021-09)
      Epileptic seizure is a neurological disorder that is prevalent in both males and females of all age ranges. Detection of epileptic seizure serves as an important role for epileptic patients as it allows the initiation ...

    • Early threat warning via speech and emotion recognition from voice calls 

      Ishtiak, Ifaz; Rahman, Mohammad Mazedur; Usmani, Md.Razaul Haque (BRAC University, 2018-12)
      The aim of this system is to identify potential cases of threats, and provide an early warning or alert to such cases. This will be based on voice such as voice chat over telecommunication networks or social media. The ...

    • Emotion detection from frontal facial image 

      Hussain, Sakib (BRAC University, 2013-10)
      Emotion recognition from facial images is a very active re-search topic in human computer interaction (HCI). In order to detect Emotion from an image I have used frontal view facial images. If computers can understand more ...

    • Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection 

      Niaz, H.M; Tajrian, Nuha; Alam, Mohammad Ahsan Ibn; Limon, Md. Shahriar Khan; Saha, Sharnit (Brac University, 2023-06)
      One of the known eye conditions that affect human retinal blood vessels is diabetic retinopathy (DR). People with diabetes are typically at significantly increased risk for this. The blood vessels in the retina are damaged ...

    • Fake currency detection using image processing method 

      Alimushwan, Munshi Md.; Mohaimin, Akiful; Islam, Rifat; Chowdhury, Shahriar (BRAC University, 2016)
      Fake notes area problem of almost every country. For country like Bangladesh it is becoming big hurdle. Fake Bangladeshi Currency of 1000 seems to have flooded the system and there is no proper way to deal with them for ...

    • Hand gesture recognition using ensemble method 

      Kowsar, Sahib; Chowdhury, Mahzabin; Mahmud, MD Safin; Haque, Shahbaj Shafin; Shifa, Asaka Akther (Brac University, 2023-05)
      Even though things have improved much more over the last century in terms of com- munication, there still is a glaring amount of communication gap between the hearing majority and the deaf community due to the lack of ...

    • Human identification using dental radiograph 

      Fahad, Salem Quddus; Hasan, Md. Nazmul; Sultana, Sharmin; Rabbani, Golam Shams (BRAC University, 2017-12)
      Dental biometrics is a very important feature in human identification. It can help greatly in Forensic Dentistry. In this paper, we present a method for identifying people based on shapes and appearances of their teeth ...

    • Music genre classification with convolutional neural network 

      Chowdhury, Masud; Tilok, Ibnul Islam; Das, Prodipta; Chowdhury, Avoy; Anas, MD. Abdullah Al Masum (Brac University, 2022-01)
      Today, Music is one of the effective forms of entertainment. Everyday new Music is being composed, and the quantity of Music is increasing day by day. So, it is essential to classify or categorize Music into different ...

    • A novel parallel texture feature extraction method using log-gabor filter and singular value decomposition (SVD) 

      Ratul, Md Aminur Rab; Raja, Sharif Ahmmad; Uddin, Jia (© 2017 ACM, 2017-01)
      Texture feature extraction consolidated with texture feature detection and feature matching solves many typical problems of image processing and computer vision; such as, texture classification, pattern recognition, object ...

    • Text classification using machine learning algorithms 

      Hasnat, Fahim; Hasan, Md. Mazidul; Khan, Nayeem Hasan; Ali, Asif (BRAC University, 8/2/2018)
      Financial, educational and communal activities produce enormous amount of data. Automatic text classification has significant application in content organization, point of view extraction, evaluation analysis, spam filtering ...

    • Traumatic meningeal enhancement detection by deep learning-based biomedical image analysis and handcrafted features extraction 

      Uddin, Mohammad Sakib; Nidhi, Nusrat Jahan; Yesmin, Sadia; Roy, Proloy Kanti (Brac University, 2024-01)
      Traumatic Meningeal Enhancement (TME) is a critical medical condition characterized by abnormal enhancement of the meninges following trauma, often observed in medical imaging studies. Traumatic meningeal injuries result ...

    • Voice impersonation detection using LSTM based RNN and explainable AI 

      Barua, Kawshik; Rahim, Abdur; Parizat, Prantozit Saha; Noor, Md.Asad Uzzaman; Jannah, Miftahul (Brac University, 2021-10)
      The advancing eld of arti cial synthetic media introduced deepfakes which made it easier to synthesize a person's voice, identical to their original voice mechanically to use it for negative means. People's voices are ...