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Browsing Project Report by Subject "Deep Learning"

Browsing Project Report by Subject "Deep Learning"

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  • An advanced deep learning approach for predicting liver cirrhosis 
    Sohag, Sohanur Rahman (Daffodil International University, 2024-01-01)
    This study provides an advanced deep learning method for predicting liver cirrhosis using a Kaggle dataset of 615 entries with a target attribute "Liver Cirrhosis Status" that classifies answers as 'Yes' (75 cases) or ...
  • An advanced deep learning approach for predicting liver cirrhosis 
    Sohag, Sohanur Rahman (Daffodil International University, 2024-01-26)
    This study provides an advanced deep learning method for predicting liver cirrhosis using a Kaggle dataset of 615 entries with a target attribute "Liver Cirrhosis Status" that classifies answers as 'Yes' (75 cases) or ...
  • An Advanced Deep Learning Approach to Detect Water Lily 
    Jamshed, Mahtab (Daffodil International University, 23-01-29)
    This project is titled “to detect water lily using deep learning” the traditional method of image recognition is to extract features manually, which cannot solve this problem well due to the complex background of flowers ...
  • Advancing sentiment analysis in Bengali: 
    Al Masud, Abdullah (Daffodil International University, 2024-01-22)
    This paper presents a comprehensive study on sentiment analysis in the Bengali language, focusing on user-generated comments from online shopping websites. Despite the significant number of Bengali speakers worldwide, ...
  • Advancing sentiment analysis in Bengali: bridging linguistic gaps in NPL with machine and deep learning models 
    Al Masud, Abdullah (Daffodil International University, 2024-01-01)
    This paper presents a comprehensive study on sentiment analysis in the Bengali language, focusing on user-generated comments from online shopping websites. Despite the significant number of Bengali speakers worldwide, ...
  • Automated Detection Leukemia Subtype Classification from Microscopic Images: A Convolutional Neural Network Approach 
    Lubna, Sheikh Bodrun Nesa (Daffodil International University, 2024-01-25)
    Leukemia is a difficult type of blood cancer which can present in a combination of multiple types, that had individual cellular and genetic abnormalities. The prevalent forms of leukemia include Acute lymphocytic leukemia ...
  • Bangla E-Mail Body to Subject Generation Using Sequence to Sequence RNNs 
    Talukder, Moyin; Alim, Md. Samiul (Daffodil International University, 22-09-13)
    The development of subjects has become one of the major problems facing deep learning and natural language processing in recent years. A brief comment on a lengthy email body is condensed in the subject generation. Our ...
  • Bangla fake news identification using deep learning and machine learning 
    Hossain, Md. Shakhawat (Daffodil International University, 2024-01-01)
    Identification of Bangla Fake News is very challenging, mostly when there is so much news from multiple online sources like social media, online news, and other online platforms. Detecting fake news is comparable in ...
  • Bangla fake news identification using deep learning and machine learning 
    Hossain, Md. Shakhawat (Daffodil International University, 2024-01-25)
    Identification Of Bangla Fake News is very challenging, mostly when there is so much news from multiple online sources like social media, online news, and other online platforms. Detecting fake news is comparable in ...
  • Bangladeshi Fresh-Rotten Fruit & Vegetable Detection Using Deep Learning Deployment in Effective Application 
    Hamim, Md.Abrar; Tahseen, Jeba (Daffodil International University, 22-09-13)
    Growing fruit and vegetables has long been a component of Bangladeshi agricultural methods. Today's rapidly changing our farming techniques for cultivate fruits and vegetables. Because our country's farmers now grow all ...
  • Bangladeshi local fish detection using deep learning techniques 
    Samiu, Asrafilil (Daffodil International University, 2024-01-01)
    This study uses deep learning techniques to provide a novel method for local fish understanding in Bangladesh. The following six native fish species are represented in the extensive dataset that was painstakingly gathered: ...
  • Bangladeshi local fish detection using deep learning techniques 
    Samiu, Asrafilil (Daffodil International University, 2024-01-26)
    This study uses deep learning techniques to provide a novel method for local fish understanding in Bangladesh. The following six native fish species are represented in the extensive dataset that was painstakingly gathered: ...
  • Battling counterfeits: cutting-edge solutions for Bangladeshi currency security 
    Hossain, Mehrab; Rahman, Mizanur (Daffodil International University, 2024-07-24)
    Counterfeit currency is a major threat to the economic integrity and security of Bangladesh, particularly with regard to high-denomination notes, including 500 and 1000 taka bills. The current study sought to achieve an ...
  • Bengali news clustering using k-means clustering based on LSA 
    Zilani, Rashedul Alam (Daffodil International University, 2024-01-24)
    Effective information retrieval and organization have become increasingly important, especially in contexts involving diverse cultural backgrounds, as the continued growth of digital content has demonstrated. The subject ...
  • Bone Fractures Classification Using Deep Learning Approaches 
    Uddin, Rahat (Daffodil International University, 2024-01-21)
    Fracture detection in medical imaging is a well-established paradigm. These days, a lot of doctors and other medical professionals utilize computer-aided diagnostic systems (CAD) to assist them diagnose a variety of ...
  • Brain hemorrhage recognition using deep learning approach 
    Shimanto, Sakib Shahariar (Daffodil International University, 2024-01-22)
    This study addresses the use of deep learning techniques, including Inception, ResNet, Xception, AlexNet, and MobileNet, for the identification of brain hemorrhages in medical imaging. Motivated by the crucial need for ...
  • Brain hemorrhage recognition using deep learning approach 
    Sakib Shahariar Shimanto (Daffodil International University, 2024-01-22)
    This study addresses the use of deep learning techniques, including Inception, ResNet, Xception, AlexNet, and MobileNet, for the identification of brain hemorrhages in medical imaging. Motivated by the crucial need for ...
  • Breast Tumor detection using deep learning 
    Atikuzzaman, Md. (Daffodil International University, 2024-01-25)
    Finding tumor areas on breast ultrasonography pictures has long been a fascinating subject. The complex architecture of breast and the presence of noise in ultrasound images sometimes make it impossible for traditional ...
  • Classification of bird species using deep learning" 
    Apu, Md Sharifuzzaman (Daffodil International University, 2024-01-24)
    Many bird species are rare to find these days, and even when they are, it might be difficult to classify them. For example, birds have different sizes, shapes, and colors depending on the situation, and they also have ...
  • Classification of Bone fractures using X-Ray images with the help of deep learning 
    Rahman, Mizanur (Daffodil International University, 2024-01-24)
    An established paradigm in the field of imaging in medical is fracture detection. These days, computer-aided diagnostic-(CAD) systems are widely used because they help physicians and other medical experts diagnose various ...

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