Browsing by Subject "LSTM"

Now showing items 1-20 of 46

    • Analysis of financial data on the time series using data from the stock market 

      Shachcha, Ifad Bhuiyan; Siam, Muhammad Ziaus (Brac University, 2022-05)
      Predicting financial data is really important for investors Often times investors do not have a proper tool to properly assess the market and forecast their predictions. Furthermore, not only investors in modern day ...

    • An Analysis on Bengali handwritten conjunct character recognition and prediction 

      Munawar, Maazin; Roy, Yagghaseni Saha; Hussain, Mohammed Mudabbir (Brac University, 2021-01)
      In the very active field of handwriting recognition, a lot of research can be found in the detection of the handwriting of various languages, especially English. However, for languages like Bengali, while they hold some ...

    • Analyzing area-wise air pollution level using machine learning for a better future 

      Sihan, Sk. Atik Tajwar; Rabbani, Maisha; Agarwala, Manish; Maliha, Sanjida Alam (Brac University, 2021-09)
      Environment consists of nature and surroundings where all living beings co-exist. Harming the environment will in turn harm all living and non-living things alike. One of the major concerns of environment pollution is ...

    • Automated image caption generator in Bangla using multimodal learning 

      Rodoshi, Mashiat Hasin; Ahmed, Moin Uddin; Ashraf, Md. Sobhan; Mim, Md. Galib Hasan; Khanam, Ashfia (Brac University, 2023-01)
      Experiencing an image on-screen is a privilege that we often seem not to care about. A visually impaired person does not have that luxury. A system that can automatically produce closed captions of an image can thus help ...

    • Automatic brain tumor segmentation using U-ResUNet chain model approach 

      Alam, Mohd Tanjeem; Nawal, Nafisa; Nishi, Nusrat Jahan; Sahan, MD Samiul; Islam, Mohammad Tanjil (Brac University, 2021-09)
      Identifying brain tumors precisely within the early stage is still a challenging problem for the medical sector consistent with recent research. In a previous research approved by Cancer. Net Editorial Board, it was ...

    • Automatic helmet-less biker detection using deep learning 

      Ratul, Md. Ibrahim; Mohon, Abdul Karim Ibne; Sarker, Md. Reduan (Brac University, 2023-09)
      When riders don’t wear a helmet while driving a motorcycle, they aren’t paying attention, leading to crashes and more deaths. The researchers utilized multiple deep-learning models to identify motorcyclists without ...

    • Bangla hate speech detection on social media using attention-based recurrent neural network 

      Das, Amit Kumar; Al Asif, Abdullah; Paul, Anik; Hossain, Md. Nur (De Gruyter, 2021-04-09)
      Hate speech has spread more rapidly through the daily use of technology and, most notably, by sharing your opinions or feelings on social media in a negative aspect. Although numerous works have been carried out in ...

    • Bangla optical character recognition from printed text using Tesseract Engine 

      Faruque, MD Yamin; Adeeb, MD Zahin; Kamal, Muhammad Maswood; Ahmed, Redwan (Brac University, 2021-01)
      Optical Character Recognition or OCR is a technology that enables us to detect and extract text from images. In our project, we are designing our OCR system around the Bangla language. This is primarily because, there are ...

    • 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 ...

    • Black swan events and machine learning 

      Tabassum, Lamia; Das, Prasenjit; Ahmed, Tasneem Bin (Brac University, 2021-01)
      Black Swan events refer to hard-to-predict and rare events that have a low probability of occurrence but have widespread impacts whenever they occur, be it positive or negative. These events can either be in the form of ...

    • Comparative analysis of machine learning models for stock price analysis across different dataset sizes 

      Srabon, Abir Alam; Abrar, Mahmudul Hasan; Rahman, Nimur; Ahmed, Washif Uddin; Hridy, Salamat Sajid (Brac University, 2023-05)
      The nature of the stock market has always been ambiguous as it constantly fluctuates for various factors. The regular fluctuations have always made it difficult for investors to invest. This paper compares six different ...

    • A comparative analysis of the different CNN-LSTM model caption generation of medical images 

      Amin, Mahzabin Yasmin Binte; Shammo, Weney Hasan; Sayed, Jawad Bin; Hossain, MD Junaied (Brac University, 2023-05)
      The intent of this paper is to make the process of interpreting and understanding information within ultrasound pictures simpler and quicker by addressing the lack of techniques for automatically deciphering medical ...

    • A computer vision based approach for stalking detection using CNN-LSTM hybrid model 

      Iqbal, Shahriar; Hasan, Murad; Faisal, Md Billal Hossain; Neloy, Md.Musnad Hossin; Kabir, Md. Tonmoy (Brac University, 2022-05)
      The next level of revolution toward a better world could involve combining human security with machine intelligence. In recent years, stalking in public areas has become a pervasive issue, and women are disproportionately ...

    • Correlating lockdowns, mortality rates and air pollution: a deep learning imbued study of COVID-19 

      Tabassum, Tahia; Rahman, Saiham; Mahmood, Moosfiqur Hassan; Siam, Md. Fahim; Mumu, Sadia Anika (Brac University, 2021-01)
      Nationwide lockdowns implemented in consequence of the devastating COVID-19 pandemic, caused noticeable improvements in air quality throughout the world. This paper implements a multivariate long-short term memory network ...

    • Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping 

      Zaman, Md. Sayeed Ibne; Kamal, Mir Ishraq; Ishan, Samiu Mostafa; Khan, Shafayat Zamil; Hossain, Samiha (Brac University, 2021-01)
      Cryptocurrency has been a fascinating topic of many over the past few years, as many people are starting to trade these currencies for big cash-outs. It is a decentralized digital currency. It is a cryptocurrency that ...

    • Data security model using deep learning and edge computing for Internet of Things (IoT) in smart city 

      Aziz, Md. Yasin; Kabbo, Tanjid Alam; Tahsin, Tasnuva; Zumme, Nadia Haque; Tahsin, Mohammad Sadman (Brac University, 2021-09)
      In the current ongoing world of the IoT (Internet of Things) devices, it is absolutely vital to have a safe, secure and reliable cyberspace. A cyberspace or network where it is free from all sorts of unethical activities ...

    • Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification 

      Tanvir, Farhan; Rahman, Tanjilur; Kamal, S M Arfa; Hassan, Mahmudul; Nazia, Nowshin (Brac University, 2024-05)
      In this thesis, for classification of sleep stages, we use deep learning techniques with the help of data from fMRI and EEG. The ConvLSTM models are applied for the fMRI data. The data for the EEG is worked on with the ...

    • Demand forecasting on supply chain using ML and NN 

      Hridi, Naoshin Anzum; Farhan, Md Sharior Hossain; Abed, Md. Junaed; Rafsan, Mohammad Nafiz Fuad (Brac University, 2022-05)
      Demand forecasting is mainly a process whereby analyzing historical sales data, strategic and operational strategies are devised in order to estimate customer demand. One of the most fundamental aspects of supply chain ...

    • Detection of Deepfake using computer vision and deep learning 

      Rahman, Anisur; Uschash, Ehteshamul Islam; Rahman, Faria; Adiba, Shihaba Jamal Chowdhury; Labib, Tahmidul (Brac University, 2023-05)
      In this era of Metaverse and technological advancement, Deepfakes are one of the most alarming concepts. Deepfakes are mostly synthetically-generated manipulated photos or videos which is created swapping a face of a ...

    • Dhaka Stock Market analysis with ARIMA-LSTM Hybrid Model 

      Arnob, Raisul Islam; Alam, Rafatul; Alam, Alvi Ebne (Brac University, 2019-08)
      This paper proposes the forecasting of correlation coe cients of Dhaka Stock Ex- change market assets required for portfolio optimization using an ARIMA-LSTM hybrid model. We have developed a robust model that encompasses ...