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Browsing DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING by Subject "Agricultural"

Browsing DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING by Subject "Agricultural"

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  • Apple and Orange Diseases Detection Using Deep Learniing Techniques 
    Faraduzzaman, G M (Daffodil International University, 23-01-18)
    We know that Bangladesh is an agricultural country where almost all people are dependent on agriculture. In today's world where everyone is health conscious, the ability to identify fruits by quality is very important in ...
  • An Application of Deep Transfer Learning To Detect Lychee Leaf Disease 
    Jisan, Tareq Rahman (Daffodil International University, 23-02-18)
    Bangladesh is a primarily agricultural nation. The majority of people depend on agriculture. Our nation of Bangladesh also heavily relies on agriculture. In the current state of affairs, it is crucial that we increase the ...
  • A Convolutional Neural Network Based Potato Leaf Diseases Detection Using Sequential Model 
    Bonik, Choyon Chandra; Akter, Flora; Rashid, Md. Harunur (23-01-29)
    One of Bangladesh's primary agricultural products is the potato. In recent decades, Bangladesh has seen a surge in the popularity of potato farms. Nonetheless, farmer’s expenses in potato production are rising as a result ...
  • Enhancing guava harvest forecasting in Bangladesh through supervised machine learning models 
    Munia, Sahela Khan (Daffodil International University, 2024-01-01)
    Accurate forecasting of guava harvest is essential for efficient resource allocation, market planning, and mitigating post-harvest losses. In Bangladesh, the guava industry faces challenges in predicting harvest yields ...
  • Identification of Rice Leaf Diseases Using CNN With Transfer Learning 
    Hossain, MD. Kawsar; Shikder, Shamim; Samit, Mohammad Fattah (Daffodil International University, 23-01-29)
    The damage done by rice leaf diseases is detrimental to our food safety and economic growth. Farmlands are being reduced day by day due to urbanization. Therefore it is highly essential to have the maximum harvest within ...
  • Local fish species classification based on computer vision 
    Showorv, Md. Mehedi Hasan (Daffodil International University, 2024-01-21)
    This research titled as “A Comprehensive Study on Multi-Class Classification and Damage Identification in Bangladeshi Fruits using Deep Neural Networks” presents a comprehensive exploration of fruit classification focusing ...
  • Performance comparison of YOLOv5 and YOLOv8 for Plumeria Leaf Gall detection 
    Mahin, Md. Shafayat (Daffodil International University, 2024-01-21)
    Leaf galls are abnormal plant growths resulting from insect parasitism, which can cause major agricultural losses if not managed in a timely manner. Precise early detection of leaf galls is crucial for enabling targeted ...
  • Plant Leaf Disease Detection Using Deep Learning Algorithms 
    Labib, Raunak Muhtasim (Daffodil International University, 2024-01-01)
    In the agricultural landscape of Bangladesh, where farming plays a crucial role in the country's economy, the well-being of plants is vital for ensuring food security. The process of photosynthesis, occurring in the ...
  • Recognizing Bangladeshi Agricultural Insects Using Machine Learning 
    Akter, Tapsara (Daffodil International University, 23-01-18)
    Recently, some work has been done on agricultural insect recognition. But a limited number of works is done on Bangladeshi agricultural insects. Pests decimate crops on a massive scale each year. To achieve high crop output, ...

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