, Signal Processing, Volume 190, January 2022
Wildfire is one of the most critical natural disasters that threaten wildlands and forest resources. Traditional firefighting systems, which are based on ground crew inspection, have several limits and can expose firefighters’ lives to danger. Thus, remote sensing technologies have become one of the most demanded strategies to fight against wildfires, especially UAV-based remote sensing technologies. They have been adopted to detect forest fires at their early stages, before becoming uncontrollable.
, Digital Signal Processing: A Review Journal, Volume 119, December 2021
The field of digital histopathology has seen incredible growth in recent years. Digital pathology is becoming a relevant tool in healthcare, industrial and research sectors to reduce the saturation of pathology departments and improve the productivity of pathologists by increasing diagnostic accuracy and reducing turnaround times. Artificial Intelligence (AI) algorithms may be used for the identification of relevant regions, extraction of features from a histological image and overall classification of images into specific classes.
, Building and Environment, Volume 203, October 2021
Monitoring the thermal comfort of building occupants is crucial for ensuring sustainable and efficient energy consumption in residential buildings. Existing studies have addressed the monitoring of thermal comfort through questionnaires and activities involving occupants. However, few studies have considered disabled people in the monitoring of thermal comfort, despite the potential for impairments to present thermal requirements that are significantly different from those of an occupant without a disability.
, Measurement: Journal of the International Measurement Confederation, Volume 171, February 2021
In the recent past, biomedical domain has become popular due to digital image processing of accurate and efficient diagnosis of clinical patients using Computer-Aided Diagnosis (CAD). Appropriate and punctual disease identification and treatment arrangement directs to enhance superiority of life and improved life hope in Alzheimer Disease (AD) patients. The cutting-edge approaches that believe multimodal analysis have been shown to be efficient and accurate are improved compared with manual analysis.
, Heliyon, Volume 7, February 2021
Background: Hippocampus segmentation on magnetic resonance imaging is of key importance for the diagnosis, treatment decision and investigation of neuropsychiatric disorders. Automatic segmentation is an active research field, with many recent models using deep learning. Most current state-of-the art hippocampus segmentation methods train their methods on healthy or Alzheimer's disease patients from public datasets. This raises the question whether these methods are capable of recognizing the hippocampus on a different domain, that of epilepsy patients with hippocampus resection.
, Current Research in Food Science, Volume 4, January 2021
Non-destructive testing techniques have gained importance in monitoring food quality over the years. Hyperspectral imaging is one of the important non-destructive quality testing techniques which provides both spatial and spectral information. Advancement in machine learning techniques for rapid analysis with higher classification accuracy have improved the potential of using this technique for food applications. This paper provides an overview of the application of different machine learning techniques in analysis of hyperspectral images for determination of food quality.
, Case Studies in Chemical and Environmental Engineering, Volume 2, September 2020
Water pollution is one of the serious threats in the society. More than 8 million tons of plastic are dumped in the oceans each year. In addition to that beaches are littered by tourists and residents all around the world. It is no secret that the aquatic life ecosystem is at a risk and soon the ratio of plastic/waste to the marine life particulary fish will be 1:1. Hence, in this paper, we have proposed a dataset known as AquaTrash which is based on TACO data set.
, Smart Health, Volume 9-10, December 2018
This work intends to develop an intelligent, four-dimensional (namely X-Y-Z plus somatosensory), partial control, and virtual-reality-enabled Tai-Chi System (VTCS). Tai-Chi is a traditional mind-body wellness and healing art, and its clinical benefits have been well documented. VTCS integrates Tai-Chi with a series of cutting-edge computer technologies including 4D sensor technology, big-data, signal processing and analysis, human body kinematics, deep learning, virtual reality, and 4D-reconstruction, etc.