Browsing by Subject "Deep Learning"
Now showing items 1-18 of 18
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An active-learning based training-schedule for biomedical image segmentation on deep neural networks
(Brac University, 2021-01)Biomedical image classification and segmentation are quite important tasks for medical diagnosis. Many Deep Neural Networks (U-Net, V-Net, etc) have been used in recent years to segment biomedical images. For classification ... -
Alzheimer’s Disease detection and classification using transfer learning techniques and ensembling operations on convolutional neural networks
(Brac University, 2021-01)Alzheimer’s disease (AD) is a neurological disease that affects the healthy cells of the brain and results in people having long-term memory loss, thinking problems, disorientation, behavioral inconsistencies and finally ... -
Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
(Brac University, 2021-06)Conventional methods of fault diagnosis for PV Systems are quite challenging and inefficient, particularly with regards to large-scale PV arrays. Early and effective diagnosis of system faults is also imperative in order ... -
Cervical Cancer Detection from Cervix Image Using Pap smear Imaging through CNN
(Brac University, 2020-04)Uterine cervical cancer is the second most regular gynecological harm around the world. The appraisal of the degree of sickness is fundamental for arranging ideal treatment. Imaging procedures are progressively utilized ... -
Comparative analysis and implementation of credit risk prediction through distinct machine learning models
(Brac University, 2021-06)Predicting the risk while lending money has always been a challenge for financial institutions. To make such decisions many banks or financial organizations follow different techniques to analyze a set of data. Manual ... -
A deep learning approach to integrate human-level understanding in a Chatbot
(2021-01)AI-powered computers like chatbots have taken over the market today to reduce human workload. Unlike humans, chatbots reply immediately, are available 24/7 and can assist several people at the same time. Due to the ... -
Deep learning in Malaria and Covid19 detection
(Brac University, 2021-01)Recent days deep learning is a promising field of research which has been used in biological applications. It is deep learning which is used in biological image detection along with the transformation of analysis data ... -
A descriptive study on development of a transfer learning based fault detection model using 2D CNN for air compressors
(Brac University, 2021-06)Fault Detection is essential for the safe and efficient operation of industrial manufacturing. Successful detection of fault features allows us to maintain a stableproduc- tion line. Therefore, establishing a reliable and ... -
Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
(Brac University, 2021-06)Parkinson’s Disease is the second most common neurological disease after Alzheimer’s Disease. The disease is incurable. However, if the disease can be detected earlier, then the consequences of it’s effect can be relieved. ... -
Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
(Brac University, 2021-06)The proper prediction of schizophrenia at an early stage can be very beneficial to those who are at risk of developing it at a severe stage later on. The early signs of schizophrenia include extreme reaction to criticism, ... -
Efficient image processing and machine learning approach for predicting retinal diseases
(Brac University, 2020-04)As the computational technology and hadrware system improved over time, the use of neural network in image processing has become more and more prominent. Soon deep learning also caught the attention of the medical sector ... -
Facial expression recognition: convolutional attentional masking network and ensemble approach
(Brac University, 2021-01)Facial expression plays a significant role in human communication. The necessity of recognizing facial expression is increasing rapidly as it can be implemented in various important fields such as in human-computer interactions, ... -
An IoT-based ambient assisted living for elderly care and monitoring in COVID-19 pandemic using arti cial intelligence and deep learning
(Brac University, 2021-06)In late 2019, a novel Coronavirus broke out from China, which has dispersed all over the globe and has taken away countless lives. Despite the fact that every person is at risk of getting infected with the virus, older ... -
Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
(Brac University, 2020-04)In this modern age, marketing strategy is becoming a new challenge. Not only the global market but also people’s choices are shifting to catch the attention of buyers. Also, based on consumer’s choice organizations are ... -
Real time action recognition from video footage
(Brac University, 2021)Crime rate is increasing proportionally with the increasing rate of the population. The most prominent approach was to introduce Closed-Circuit Television (CCTV) camera-based surveillance to tackle the issue. Video ... -
Shield key: a deep learning process for the generation of public & private keys using hybrid architecture in blockchain
(Brac University, 2021-06)The fast-growing cryptocurrency system is changing the financial world with its ensured blockchain technology. It’s specific use in expounding cryptocurrencies is highly acknowledged in the modern world, although the ... -
Smart companion agent for mental well-being through Deep Learning and NLP
(Brac University, 2021-01)Mental disorders are an unfortunate reality among the general population nowadays. Conditions like anxiety; depression may seem trivial on the surface but have serious consequences on an individual’s life. These disorders ... -
Traffic sign recognition using deep learning
(Brac University, 2019-12)Traffic sign recognition plays a significant role in modern automated driver assisting systems and showing information about safety measures. It is a technology that allows users to recognize traffic signs in real-time, ...
