Now showing items 1-15 of 15

    • Automatic waste classification using deep learning and computer vision techniques 

      Akash, MD.; Shama, Umme Sabiha; Dibash, Dey; Ghosh, Ria (Brac University, 2023-03)
      Waste management refers to a system that starts with classifying different kinds of waste and gradually managing it from its inception to its final disposal. Labeling waste in a proper manner can ensure the best outcome ...
    • Demystifying black-box learning models of rumor detection from social media posts 

      Tafannum, Faiza; Shopnil, Mir Nafis Sharear; Salsabil, Anika; Ahmed, Navid (BRAC University, 2021-09)
      Social media and its users are vulnerable to the spread of rumors, therefore, protect ing users from these rumors spread is extremely important. This research proposes a novel approach for rumor detection in social media ...
    • Detection of skin cancer using Convolutional neural network 

      Ahsan, Abu Sa-adat Mohamed Moon-Im Al; Alif, Shadman Monsur; Kibria, Junaid Bin; Gomes, Prince Elvis (Brac University, 2019-10)
      One of the most common and fatal cancer in the universe is skin cancer which arise from skin of epidermis, the topmost layer of the skin, it can happen anywhere in the body. We can find out the cancer by early detection. ...
    • Eve-teasing detection from video footage using computer vision and artificial intelligence 

      Rapheo, Abdullah; Billah, A.T.M. Masum; Islam, Lamisha; MD Yahia Mahim, Abu Shale (Brac University, 2023-01)
      We present computer vision approaches combined with machine learning techniques to detect eve-teasing from any video material, which may be used in any situa tion. Eve teasing is a colloquial term for public sexual ...
    • Factors associated with antifungal resistance and the recent development in detection & treatment: a review 

      Madhuri, Srijila (Brac University, 2023-06)
      Antifungal resistance has become a growing concern in recent years, as it has become increasingly difficult to treat fungal infections due to the emergence of drug-resistant organisms. The prevalence of antifungal resistance ...
    • Fraud detection in E-commerce using natural language processing 

      Kabir, Iftekhar; Momo, Marium Khan; Tazrian, Tahsin (Brac University, 2023-01)
      Electronic commerce sometimes referred to as e-commerce is a type of business that enables both businesses and private individuals to purchase and sell products and services online. E-commerce in Bangladesh is thriving ...
    • Mitigating DDoS attacks using a resource sharing network 

      Khan, Farabi Fardin; Hossain, Nafis Mohaimin; Mahmud, Toushif; Anwar, Sad Bin; Islam, Sirajul (Brac University, 2021-10)
      Cloud computing is crucial to the internet just as air is crucial to breathing. Most users do not even come to think how the cloud architecture is one of the giant pillars on which the entire internet and all its related ...
    • Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing 

      Tasnim, Sadia; Sarker, Sukarna; Bhoumik, Partha; Al Maruf, K.M. Abdullah; Rahman Hasib, MD Mahfuzur (Brac University, 2023-01)
      Despite various preventative measures and therapies, the COVID-19 pandemic has exposed a number of weaknesses and vulnerabilities in global health systems, particularly in low and middle-income countries that may have ...
    • Novel approach to detect hate speech and profanity on online platforms 

      Pritha, Barha Meherun; Islam, Samin; Alam, Tabassum (Brac University, 2021-09)
      Hate speech is becoming more prominent and dominant in the virtual world, with the popularity of social media increasing day by day. People nowadays have various online platforms where they can express their hatred and ...
    • PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework 

      Rahman, Tahsinur; Ahmed, Nusaiba; Monjur, Shama; Haque, Fasbeer Mohammad; Kabir, Naweed (Brac University, 2023-01)
      As the world is moving more and more towards a digital era, a great majority of data is transferred through a famous format known as PDF. One of its biggest obstacles is still the age-old problem: malware. Even though ...
    • Plant disease detection using convolutional neural network 

      Hossain, Mohammad Shifat; Noor, Fatin Ishraq; Ali, Mir Ayman; Alam, Ra ul (Brac University, 2020-04)
      Rice is a staple crop of Bangladesh and many metric tons of it are being destroyed every year due to diseases. If the diseases can be efficiently and accurately classified ed and recognized at early stage, the farmers ...
    • Real time performance analysis on DDoS attack detection using machine learning 

      Suvra, Debashis Kar; Sen, Tanusree; Mou, Maysha Maliha; Rahman, Asifur (Brac University, 2020-04)
      In recent years, Distributed Denial of service (DDoS) attacks have led to a tremendous financial loss in some industries and governments. Such as banks, universities, news and media publications, financial services, ...
    • Real-time garments defects detection at the sewing phase to optimize waste cost using YOLOv7, YOLOv7x, YOLOv7-w6 and Pytorch 

      Uddin, Md. Minhaz; Foysal, Sadi Mahmud; Rahman, Sadia; Risti, Nushara Tazrin; Sarmin, Sanzeda Akter (Brac University, 2023-01)
      In the era of computer vision to overcome challenges, the introduction of the YOLO model revolutionized real-time computer vision approaches. In the garment industry, the inception of products plays a significant role ...
    • Recent advancement on breast cancer detection and treatment 

      Rahman, Sanjida (Brac University, 2022)
      Breast cancer is the most common cancer in women compared to men. The genetic and epigenetic factors, food habit, lifestyle, age vulnerability, poor diagnosis system, and substandard treatment set-up are linked to the ...
    • Skin disease detection and classification using deep learning 

      Shuvon, Mehedi Hasan; Sadia, Rowshanara; Shormi, Shanjida Habib; Arafin, Umma Tania; Chowdhury, Md. Rawha Mikdad (Brac University, 2022-01)
      Skin Diseases have been the primary focus of this study, as they are one of the most lethal diseases if not diagnosed and treated early. The research will enable the fields of Medical Science and Computer Science to ...