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Cassava leaf disease classification using deep learning and convolutional neural network ensemble
(Brac University, 2022-01)
Cassava is a high-protein and nutrient-dense plant, notably inside the leaves. Cassava
is often used as a rice alternative. Pests, viruses, bacteria, and fungus may cause
a variety of illnesses on cassava leaves. This ...
Myocardial infarction detection using ECG signal applying deep learning techniques - ConvNet, VGG16, InceptionV3 and MobileNet
(Brac University, 2022-01)
Due to our unhealthy diets and the consumption of enhanced cholesterol in our
daily lives, our health has become vulnerable and at risk of different types of cardiac
diseases. The most common of them is Myocardial ...
An efficient deep learning approach to detect skin cancer using image data
(Brac University, 2023-01)
We propose and demonstrate an efficient deep learning approach to classify skin can cer using image data. The proposed approach is composed of several stages which
are data acquisition, preprocessing and classification. ...
An interpretable deep learning approach to detect Alzheimer using MRI images
(Brac University, 2023-01)
Alzheimer’s disease (AD) is a serious neurological condition that causes loss of long term memory, cognitive difficulties, disorientation, inconsistent behavior, and even tually death. Also, AD is caused by the destruction ...
Automatic brain tumor segmentation using U-ResUNet chain model approach
(Brac University, 2021-09)
Identifying brain tumors precisely within the early stage is still a challenging problem
for the medical sector consistent with recent research. In a previous research
approved by Cancer. Net Editorial Board, it was ...
Corn leaf disease detection using deep convolution neural network
(Brac University, 2023-01)
Detecting corn leaf diseases helps farmers identify and treat impacted crops. Early
disease identification reduces crop loss. Manual leaf diagnostic imaging takes time
and is prone to mistakes. This thesis proposes a ...
Pest detection system using machine learning techniques
(Brac University, 2022-01)
Countries like Bangladesh yield a significant portion of their economy from their
agricultural sector. Agricultural pests, on the other hand, have a significant impact
on both agricultural production and crop storage. ...
Prostate cancer detection using deep learning neural network with transfer learning approach
(Brac University, 2021-10)
Prostate cancer is a ubiquitous form of cancer detected among men all over the
world. It is currently the second leading cause of cancer death worldwide among
men. Research shows that about 11% of men worldwide are ...
Visual object classification from fMRI data
(Brac University, 2022-01)
Computing devices were once limited in just calculating arithmetic. Whereas, in
modern computing, complex task like object classi cation or recognition has become
so popular that even our smart devices cannot be thought ...
A color vision approach considering Reflection Co efficient based on Autoencoder techniques using deep neural networks
(Brac University, 2021-09)
Color vision approach using auto encoded technique is an effective way to detect
objects. This approach considers various factors like movement detection, size and
shape detection, color detection etc. Here we have ...