Multi-Class Gaze Detection in a Dynamic Environment
Developing AI tools to identify areas of interest within a dynamic field of view is essential for
objective behavioural evaluation of drivers. Video image classification and specifically …
objective behavioural evaluation of drivers. Video image classification and specifically …
A comparative analysis of loss functions in segmentation of medical images with highly imbalanced class distribution: An experimental study for deep nuclei …
As is widely known, anatomical structures on medical images can be segmented
successfully with the deep learning-based approaches. In such tasks, the performances of …
successfully with the deep learning-based approaches. In such tasks, the performances of …
Size-based adaptive instance pruning for refined segmentation of cell nuclei in histology images
In this paper, a size-based instance pruning approach, which can be used for more accurate
segmentation of cell nuclei in histology images and can be adapted to cell types, is …
segmentation of cell nuclei in histology images and can be adapted to cell types, is …
Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
M Erezman, T Dziubich - European Conference on Advances in Databases …, 2024 - Springer
Accurate segmentation of cellular nuclei is imperative for various biological and medical
applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline …
applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline …
Automatic Identification of Adenoid Hypertrophy via Ensemble Deep Learning Models Employing X-ray Adenoid Images
Adenoid hypertrophy, characterized by the abnormal enlargement of adenoid tissue, is a
condition that can cause significant breathing and sleep disturbances, particularly in …
condition that can cause significant breathing and sleep disturbances, particularly in …
[HTML][HTML] 基于改进UNet 模型的眼球超声图像分割算法研究
赵兵 - Modeling and Simulation, 2024 - hanspub.org
在医学图像分割领域, 提高分割性能一直是一个具有挑战性的任务. 超声图像具有边缘模糊,
噪声污染等缺点, 为了解决眼球超声图像分割结果不理想这一难题, 本文提出了一种基于UNet …
噪声污染等缺点, 为了解决眼球超声图像分割结果不理想这一难题, 本文提出了一种基于UNet …
An Ensemble Learning Based Nuclei Segmentation: Using Base Deep Learning Models with Different Loss Functions
Nuclei instance segmentation is a crucial task for computational pathology, as it enables
precise analysis of nuclear morphology, aiding in the early diagnosis and accurate …
precise analysis of nuclear morphology, aiding in the early diagnosis and accurate …
Advanced Brain Tumor Segmentation and Detection using YOLOv8
BDK Reddy, PBK Reddy, L Priya - 2024 2nd International …, 2024 - ieeexplore.ieee.org
The state-of-the-art YOLOv8 deep learning model is used in this project to change how brain
tumors are found and grouped in MRI scans. YOLOv8 can now tell the difference between …
tumors are found and grouped in MRI scans. YOLOv8 can now tell the difference between …
Segmentation of Cell Nuclei in Histology Images with Vision Transformer Based U-Net Models
This paper presents a research study on the performance analysis of vision transformer-
based UNet models in semantic and instance segmentation of cell nuclei in colon histology …
based UNet models in semantic and instance segmentation of cell nuclei in colon histology …
Identification of Myeloproliferative Neoplasms using Deep Learning
S Abraham, B Penchalareddy… - … Women in Data …, 2024 - ieeexplore.ieee.org
Myeloproliferative Neoplasms (MPNs) are a heterogeneous group of disorders
characterized by proliferation of one or more hematologic cell. These myeloproliferative …
characterized by proliferation of one or more hematologic cell. These myeloproliferative …