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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 ...
Greenhouse monitoring and harvesting mobile robot with 6DOF manipulator utilizing ROS, inverse kinematics and deep learning models
(Brac University, 2022-01-20)
The rapid climate change and scarcity of fertile land has been a global concern recently. To sustain the food supply its high time to think about the modern way of cultivating which is greenhouse. Taking these changes as ...
X-Ray classification to detect COVID-19 using ensemble model
(Brac University, 2021-06)
Diagnosis with X-Rays and other forms of medical images has soared to new heights
as an alternative visual Covid infection detector. Radiographic images, primarily
CT scans and X-Rays images play massive roles in assisting ...
Skin cancer detection and classification using multiple optimized deep convolutional neural network
(Brac University, 2022-05)
This work tries to detect skin cancer and classify its type using datasets containing
labeled images and classes, using pre-trained CNN models and merged
pre-trained CNN models. Skin cancer is an abnormal growth of skin ...
An efficient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
(Brac University, 2021-01)
Among the most convenient bacteriological assessments for the diagnosis and treatment with several health complications is the chest X-Ray. The World Health Organization (WHO) estimates, for instance, that pneumonic plague ...
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 ...
Detecting Deepfake images using deep convolutional neural network
(Brac University, 2021-09)
In recent years, advancement in the realm of machine learning has introduced a
feature known as Deepfake pictures, which allows users to substitute a genuine face
with a fake one that seems real. As a result, distinguishing ...
Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
(Brac University, 2020-04)
Diseases in Tomato mostly on the leaves affect the reduction of both the standard
and quantity of agricultural products. Several diseases such as bacterial spot, early
blight, late blight, leaf mold, septoria leaf spot, ...