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Segmentation based Kidney Tumor Classification using Deep Neural Network
(Brac University, 2022-01)
Kidney disease is one of many severe chronic disease that a person can have. Early
detection of this disease can be pivotal for proper treatment. Different neural net works have proven to be useful in disease prediction ...
Lossless segmentation of Brain Tumors from MRI images using 3D U-Net
(Brac University, 2022-01)
2D computer vision and activities related to medical image analysis are remarkably
guided with the help of Convolutional Neural networks (CNNs) in recent years.
Since a chief portion in the available clinical imaging ...
Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
(Brac University, 2023-01)
The use of machine learning models has greatly enhanced the capability to rec ognize patterns and draw conclusions. However, due to their black-box nature, it
can be difficult to comprehend the factors that affect their ...
Handwritten character recognition using neural network
(Brac University, 2020-04)
Handwritten character recognition is a process of a system to access handwritten material from various sources such as paper records, photographs, touch screen apps, etc. The identification of handwritten and electronic ...
Detection of pneumonia from chest X-ray images using machine learning
(Brac University, 2023-05)
A bacterial infection is the cause of the lung condition known as pneumonia. An essential component of a successful treatment procedure is early diagnosis. Without early diagnosis, pneumonia can be severe or even can cause ...
Image translation of Bangla and English sign language to written language using convolutional neural network
(Brac University, 2022-05)
One particular thing that differentiates humans from other species is their abilities to
interact. To communicate with others, humans invented languages as units. There
are 6500 Languages in this world for people of ...
An Efficient deep learning approach to detect Brain Tumor using MRI images
(Brac University, 2021-10)
A brain tumor is the development of mutated cells in the human brain. Many di er-
ent types of brain tumors exist nowadays. According to researchers and physicians,
some brain tumors are non-cancerous while some are ...
Application of deep convolutional neural network in multiclass skin cancer classification using custom CNN architecture
(Brac University, 2023-05)
Skin diseases represent a significant global health concern, and prompt and pre-
cise diagnosis is necessary for efficient treatment. Convolutional Neural Networks
(CNNs), in particular, have shown tremendous promise in ...
An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
(Brac University, 2022-05)
Optical Coherence Tomography (OCT) is an effective approach for diagnosing retinal
problems that can be used in combination with traditional diagnostic testing
methods. We developed and implemented a deep Convolutional ...
U-net Based Autonomous Fetal Segmentation From 2D and 3D Ultrasound Images
(Brac University, 2022-05)
There are various biometric parameters of the fetus that need to be evaluated to
monitor prenatal diagnosis during pregnancy. Biometric parameters such as head
circumference, abdominal circumference, cortical volume, the ...