Browsing by Subject "Deep learning (Machine learning)."
Now showing items 1-19 of 19
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Comprehensive analysis and development of deep learning models for Bengali character’s spectrogram image classification in child speech: introduction of spectro SETNet
(Brac University, 2024-05)In a rapidly developing linguistic technology, the key role of phoneme recognition consists of understanding language and language learning. The research will be framed where a recognition system is developed for the ... -
Credit card fraud detection through advanced machine learning techniques
(BRAC University, 2024-10)Nowadays, digital and electronic transactions and electronic payments systems in modern days have become convenient but now it is a major challenge to face credit card fraud. Modern fraud patterns are so complex and ... -
Detection of pulmonary diseases from chest X-ray images using deep learning model
(BRAC University, 2024-10)Deep learning models are important in efficiently identifying different pulmonary diseases from Chest X-ray Images (CXRs). Pneumonia is one of the most common lung diseases that cause death. Especially, stage 4 pneumonia ... -
Determining intensity of mental state of an unsound individual through text using ML
(BRAC University, 2024-10)This research investigates the application of machine learning to detect and classify the intensity of various mental health conditions through text analysis. By analyzing user-generated statements, the study aims to ... -
Divide2Conquer (D2C): a comprehensive study on decentralized overfitting remediation in deep learning
(BRAC University, 2024-10)Overfitting remains a persistent challenge in deep learning, primarily attributed to data outliers, noise, and limited training set sizes. This thesis presents Divide2Conquer (D2C), a novel technique designed to address ... -
An efficient deep learning-based approach for Glioblastoma detection from MRI images
(BRAC University, 2024-10)In essence, an abnormal increase of brain cells is referred to as a brain tumor. Tumors come in two varieties: benign (non-cancerous) and malignant (cancerous). Cancerous tumors can originate in the brain itself (Primary) ... -
Enhancing multiclass brain tumor classification using deep learning: leveraging superior imaging representations to improve inferior modality performance
(Brac University, 2024-05)The early and accurate diagnosis of brain tumors is a critical challenge in medi cal imaging, significantly impacting treatment outcomes and patient survival rates. Despite the advancements in imaging technologies, the ... -
From impersonation to authentication: techniques for identifying deep fake voices
(BRAC University, 2024-10)The proliferation of fake voices has become a concerning issue, making it increasingly challenging to distinguish between authentic and fabricated audio recordings. Notable examples include the replication of the voices ... -
Identifying code-mixed and code-switched hateful remarks on social media using NLP
(Brac University, 2024-05)Online bullying has prevailed for years in the vast cesspool that is commonly known as the online social media. Increasing use of social media and online communication has led to a rise in cyberbullying– which is often ... -
Identifying hate speech of Bangla language text using natural language processing
(Brac University, 2024-01)In this era of the internet, sharing information through social media has provided significant benefits to humans. People can easily access and observe others’ lifestyles and work, as well as make comments or share ... -
Identifying malnutrition from facial features of children using deep dearning
(BRAC University, 2024-10)Malnutrition remains a significant global health issue, particularly affecting children, leading to severe developmental challenges. Current diagnostic methods are often inefficient, relying on time-consuming physical ... -
Image processing and deep learning for space telescope images: an exploratory data analysis approach
(BRAC University, 2024-01)Exposing patterns in cosmic affairs from space telescope images is performed by a strong methodology configured by Exploratory Data Analysis (EDA) and advanced image processing techniques. This research utilizes machine ... -
Optimized deep learning model for plant disease detection using leaf images
(Brac University, 2024-10)Accurate and timely plant disease detection is very much essential in crop health and agricultural yield. The work below describes an improved deep learning model for the classification of plant diseases through images. ... -
Predictive analysis of non fungible token price using deep learning
(Brac University, 2023-09)A form of digital asset called Non-fungible tokens can represent a wide range of objects, such as pieces of art, collectibles, and in-game items. Non-fungible tokens are also commonly referred to by their acronym, NFTs. ... -
Sales forecasting using machine learning
(BRAC University, 2024-10)In today’s aggressive and fast-paced economy, the ability to forecast sales accurately and effectively denotes a proper utilization of the available resources in planning. Typical sales forecasting methods fail quite ... -
Structural crack classification and grading after disaster: a supervised learning approach
(BRAC University, 2024-10)A structure can be cracked by various disastrous events (for example: flood, cyclone, volcanic eruption, earthquake, fire outbreak). When a disastrous event occurs in an area, a lot of structures get damaged within a ... -
Tracing subtle patterns: early detection of Anorexia in social media using contextualized BERT embeddings and deep learning
(BRAC University, 2024-10)In a world where the usage of social media is prevalent, it is important to acknowledge the fact that these social platforms have been increasingly used to share private matters with the public eye, which may sometimes ... -
TRI-FED-RKD: integrating forward-reverse distillation with SNN and CNN within federated learning using tri layer hierarchical aggregation based architecture
(BRAC University, 2024-10)Federated Learning (FL) is a decentralized machine learning paradigm that enables training a global model across numerous edge devices while preserving data privacy. However, FL faces significant challenges, particularly ... -
Unveiling agricultural insights: leveraging deep learning for enhanced diagnostic accuracy in Maize disease detection with explainable artificial intelligence
(BRAC University, 2024-10)Maize is a vital crop that feeds over a billion people worldwide and supports numerous industries. However, maize production is threatened by devastating plant diseases such as Maize Lethal Necrosis (MLN) and Maize Streak ...
