Browsing by Subject "Artificial neural network"
Now showing items 1-7 of 7
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Connected hidden neurons (CHNNet): an artificial neural network for rapid convergence
(Brac University, 2023-09)Despite artificial neural networks being inspired by the functionalities of biological neural networks, unlike biological neural networks, conventional artificial neural networks are often structured hierarchically, which ... -
Crop prediction based on geographical and climatic data using machine learning and deep learning
(BRAC University, 2018-12)Agriculture is the basic source of food supply in all the countries of the world—whether underdeveloped, developing or developed. Besides providing food, this sector has contributions to almost every other sector of a ... -
Early detection of breast cancer using machine learning
(Brac University, 2018-12)Breast cancer is the most common cancer among women but in can occur in both the genders. It is accountable for an appalling number of deaths worldwide. In a particularly low-resource developing country like Bangladesh, ... -
Early detection of parkinson’s disease using image processing and artificial neural network
(BRAC University, 2018-04)Early detection of Parkinson‟s Disease (PD) is very crucial for effective management and treatment of the disease. Dopaminergic images such as Single Photon Emission Tomography (SPECT) using 123I-Ioflupane can substantially ... -
A machine learning-based approach for data analysis to ascertain suicidal individuals from Social media users
(Brac University, 2023-01)In this research, we propose a hybrid model for predicting suicide risk from text data that incorporates BERT, VADER, and a Random Forest classifier for sentiment analysis. This model aims to identify individuals who may ... -
PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
(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 ... -
A performance comparison between machine learning models on zero-day attack detection
(Brac University, 2021-01)Traditional IDS has been shielding against cyber threats for many years but it falls short on detecting zero-day attacks. These are the attacks that are unique with unknown attack patterns and mutating attack signatures ...
