The College of Engineering and Computer Science: Recent submissions
Now showing items 21-40 of 59
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A Weighted Viewport Quality Metric for Omnidirectional Images
(2020-01-01)Thanks to the ability to bring immersive experiences to users, Virtual Reality (VR) technologies have been gaining popularity in recent years. A key component in VR systems is omnidirectional content, which can provide ... -
A systematic review of the use of topic models for short text social media analysis
(2023-03-14)Recently, research on short text topic models has addressed the challenges of social media datasets. These models are typically evaluated using automated measures. However, recent work suggests that these evaluation measures ... -
A Survey on Deep Learning Advances and Emerging Issues in Pneumonia and COVID19 Prediction
(2022-01-17)As the COVID19 pandemic evolves and coronavirus mutates to different variants, a high workload falls on the shoulders of doctors and radiologists. Identifying COVID19 through X-ray and Computed Tomography (CT) scanning in ... -
A Novel Transparency Strategy-based Data Augmentation Approach for BI-RADS Classification of Mammograms
(2022-03-20)Image augmentation techniques have been extensively studied to enhance the performance of deep learning (DL) algorithms in mammography classification tasks. Recent advancements have demonstrated the effectiveness of image ... -
Learning to diagnose common thorax diseases on chest radiographs from radiology reports in Vietnamese
(2022-10-07)Deep learning, in recent times, has made remarkable strides when it comes to impressive performance for many tasks, including medical image processing. One of the contributing factors to these advancements is the emergence ... -
Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks
(2021-10-17)Chest radiograph (CXR) interpretation is critical for the diagnosis of various thoracic diseases in pediatric patients. This task, however, is error-prone and requires a high level of understanding of radiologic expertise. ... -
Use of a convolutional neural network and quantitative ultrasound for diagnosis of fatty liver
(2020-10-30)Quantitative ultrasound (QUS) was used to classify rabbits that were induced to have liver disease by placing them on a fatty diet for a defined duration and/or periodically injecting them with CCl4. The ground truth of ... -
Understanding Hierarchical Processes
(2022-11-22)Hierarchical stochastic processes, such as the hierarchical Dirichlet process, hold an important position as a modelling tool in statistical machine learning, and are even used in deep neural networks. They allow, for ... -
VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
(2021-06-24)Radiographs are used as the most important imaging tool for identifying spine anomalies in clinical practice. The evaluation of spinal bone lesions, however, is a challenging task for radiologists. This work aims at ... -
Trend Analysis of Forest Fire in Pahang, Malaysia from 2001-2021 with Google Earth Engine Platform
(2022-12)Remote sensing imagery is one of the cost-efficient solutions to observe forest fire occurrence in a particular region. With the accessibility of more public remote sensing data, researchers and field experts can exploit ... -
Towards an Overall QoE Model for 360-Degree Video
(2021-01-13)Although 360-degree video is becoming more and more popular on the Internet, understanding of Quality of Experience (QoE) of 360-degree video is still limited. In this paper, we aim to investigate for the first time the ... -
Toward forecasting future day air pollutant index in Malaysia
(2020-10-14)The association of air pollution and the magnitude of adverse health effects are receiving close attention from the world. The effects of air pollution were found to be most significant for children, elderly, and patients ... -
SEGTRANSVAE: Hybrid CNN-Transformer with Regularization for Medical Image Segmentation
(2022)Current research on deep learning for medical image segmentation highlights limitations in learning either global semantic information or local contextual information effectively. To address these challenges, this paper ... -
SDN – based Dynamic Bandwidth Allocation for Multiple Video-on-Demand Players over HTTP
(2019)Nowadays, HTTP adaptive streaming (HAS) has become the standard for video streaming over multimedia networks. However, HAS alone cannot ensure a seamless viewing experience. The adaptation of HAS in network management faces ... -
Scalable 360 Video Streaming using HTTP/2
(2019-07)360-degree video is the primary content type in Virtual Reality, offering users an immersive viewing experience. This paper introduces a novel adaptation method for streaming 360-degree video over HTTP/2, aimed at enhancing ... -
Retina-based quality assessment of tile-coded 360-degree videos
(2022-06-21)Nowadays, omnidirectional content, which delivers 360-degree views of scenes, is a significant aspect of Virtual Reality systems. While 360 video requires a lot of bandwidth, users only see visible tiles, therefore a large ... -
QoE Models for Adaptive Streaming: A Comprehensive Evaluation
(2022-05-13)Adaptive streaming has become a key technology for various multimedia services, such as online learning, mobile streaming, Internet TV, etc. However, because of throughput fluctuations, video quality may be dramatically ... -
Neural Radiance Projection
(2022-03-20)The proposed method, Neural Radiance Projection (NeRP), addresses three fundamental challenges in training convolutional neural networks for X-ray image segmentation: handling limited or missing human-annotated datasets, ... -
Network-aware Prefetching Method for Short-Form Video Streaming
(2022-09-07)Recent years have witnessed the rising popularity of short-form video platforms such as TikTok. Unlike conventional videos, short-form videos are significantly shorter, and users frequently switch between content. Therefore, ... -
Improving multi-label text classification using weighted information gain and co-trained multinomial naïve bayes classifier
(2022)Over recent years, the emergence of electronic text processing systems has generated a vast amount of structured and unstructured data, thus creating a challenging situation for users to rummage through irrelevant information. ...
