Monte carlo dropblock for modelling uncertainty in object detection

K Deepshikha, SH Yelleni, PK Srijith… - arXiv preprint arXiv …, 2021 - arxiv.org
With the advancements made in deep learning, computer vision problems like object
detection and segmentation have seen a great improvement in performance. However, in …

A comparative analysis of machine learning algorithms for classification purpose

V Sheth, U Tripathi, A Sharma - Procedia Computer Science, 2022 - Elsevier
A few of the popular data-mining techniques are clustering, classification, and association.
The classification process simplifies the process of identifying and accessing data …

Brain tumor detection using deep learning and image processing

AS Methil - … conference on artificial intelligence and smart …, 2021 - ieeexplore.ieee.org
Brain Tumor Detection is one of the most difficult tasks in medical image processing. The
detection task is difficult to perform because there is a lot of diversity in the images as brain …

[PDF][PDF] Brain Tumor Auto-Segmentation on Multimodal Imaging Modalities Using Deep Neural Network.

E Hossain, MS Hossain, MS Hossain… - … , Materials & Continua, 2022 - researchgate.net
Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for
extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and …

Mathematical assessment of machine learning models used for brain tumor diagnosis

D Uzun Ozsahin, EP Onakpojeruo, B Uzun… - Diagnostics, 2023 - mdpi.com
The brain is an intrinsic and complicated component of human anatomy. It is a collection of
connective tissues and nerve cells that regulate the principal actions of the entire body …

Lung cancer disease diagnosis using machine learning approach

S Mukherjee, SU Bohra - 2020 3rd International Conference on …, 2020 - ieeexplore.ieee.org
The analysis and study of lung diseases has been the most intriguing investigation zone of
medical experts from early days to the present day. To address this concern, a diagnosis …

Automatic detection of brain tumor using deep learning algorithms

R Sangeetha, A Mohanarathinam… - 2020 4th …, 2020 - ieeexplore.ieee.org
Brain tumor is the result of an abnormal growth of cells, which reproduce themselves in an
uncontrolled manner. This type of tumour is diagnosed through Magnetic Resonance …

Classification of Parkinson's disease using speech attributes with parametric and nonparametric machine learning techniques

S Sharanyaa, PN Renjith… - 2020 3rd international …, 2020 - ieeexplore.ieee.org
Parkinson's disease is a neurological disorder that affects the central nervous system which
results in improper functioning of body movements including difficulty in speaking, walking …

SVM model based computerized bone cancer detection

B Jabber, M Shankar, PV Rao… - 2020 4th International …, 2020 - ieeexplore.ieee.org
Among the many types of cancers, bone cancer is one with which most of the deaths occur
in the world. Around 10000 deaths are occurring in a year in India due to bone cancer. Bone …

Early detection of brain stroke using machine learning techniques

V Krishna, JS Kiran, PP Rao, GC Babu… - 2021 2nd International …, 2021 - ieeexplore.ieee.org
The brain is the most complex organ in the human body. Brain Stroke is a long-term
disability disease that occurs all over the world and is the leading cause of death. A stroke …