Ensure worker safety in the industry is crucial. Despite efforts to improve safety, statistics show a plateau in the reduction of these accidents in recent years. To decrease the number of accidents, compliance with established industrial safety standards and regulations by competent authorities must be ensured, including the use of Personal Protective Equipment (PPE). PPE usage...
Anisotropic diffusion is one of the most effective methods used in image processing. It can be used to eliminate the small textures of an image while preserving its significant edges. In this paper, a new anisotropic diffusion filter is proposed based on a fractional calculus kernel rather than integer kernel to improve the overall performance of the filter. Integer and...
This paper presents a new Edge-AI algorithm for real-time and multi-feature (social distancing, mask detection, and facial temperature) measurement to minimize the spread of COVID-19 among individuals. COVID-19 has extenuated the need for an intelligent surveillance video system that can monitor the status of social distancing, mask detection, and measure the temperature of faces...
Deep convolutional neural networks (CNNs) have shown tremendous success in the detection of objects and vehicles in recent years. However, when using CNNs to identify real-time vehicle detection in a moving context remains difficult. Many obscured and truncated cars, as well as huge vehicle scale fluctuations in traffic photos, provide these issues. To improve the performance of...
For target detection tasks in complicated backgrounds, a deep learning-based radar target detection method is suggested to address the problems of a high false alarm rate and the difficulties of achieving high-performance detection by conventional methods. Considering the issues of large parameter count and memory occupation of the deep learning-based target detection models, a...
New and interesting uses for portable devices include the creation and viewing of 3D models and 360-degree photos of real landscapes. To provide a 3D model and a 360-degree view of a scenario, these apps search for real-time rendering and presentation. This study examines the impact of real-time image processing on movements in camera view and the application of optical flow...
Facial expression recognition (FER) is utilized in various fields that analyze facial expressions. FER is attracting increasing attention for its role in improving the convenience in human life. It is widely applied in human–computer interaction tasks. However, recently, FER tasks have encountered certain data and training issues. To address these issues in FER, few-shot learning...
The recent research effort aiming to provide a royalty-free video format resulted in AOMedia Video 1 (AV1), which was launched in 2018. AV1 was developed by the Alliance for Open Media (AOMedia), which groups several major technology companies such as Google, Netflix, Apple, Samsung, Intel, and many others. AV1 is currently one of the most prominent video formats and has...
This paper presents a GPU-based parallelisation of an optimised versatile video decoder (VVC) adaptive loop filter (ALF) filter on a resource-constrained heterogeneous platform. The GPU has been comprehensively utilised to maximise the degree of parallelism, making the programme capable of exploiting the GPU capabilities. The proposed approach enables to accelerate the ALF...
Automatic crowd counting using density estimation has gained significant attention in computer vision research. As a result, a large number of crowd counting and density estimation models using convolution neural networks (CNN) have been published in the last few years. These models have achieved good accuracy over benchmark datasets. However, attempts to improve the accuracy...
Beam hardening (BH) is one of the major artifacts that severely reduces the quality of computed tomography (CT) imaging. This BH artifact arises due to the polychromatic nature of the X-ray source and causes cupping and streak artifacts. This work aims to propose a fast and accurate BH correction method that requires no prior knowledge of the materials and corrects first and...
Image dehazing methods can restore clean images from hazy images and are popularly used as a preprocessing step to improve performance in various image analysis tasks. In recent times, deep learning-based methods have been used to sharply increase the visual quality of restored images, but they require a long computation time. The processing time of image-dehazing methods is one...
The detection of multi-scale pedestrians is one of the challenging tasks in pedestrian detection applications. Moreover, the task of small-scale pedestrian detection, i.e., accurate localization of pedestrians as low-scale target objects, can help solve the issue of occluded pedestrian detection as well. In this paper, we present a fully convolutional neural network with a new...
As seen in the COVID-19 pandemic, one of the most important measures is physical distance in viruses transmitted from person to person. According to the World Health Organization (WHO), it is mandatory to have a limited number of people in indoor spaces. Depending on the size of the indoors, the number of persons that can fit in that area varies. Then, the size of the indoor area...
The novel coronavirus pneumonia (COVID-19) is the world’s most serious public health crisis, posing a serious threat to public health. In clinical practice, automatic segmentation of the lesion from computed tomography (CT) images using deep learning methods provides an promising tool for identifying and diagnosing COVID-19. To improve the accuracy of image segmentation, an...
The versatile video coding standard H.266/VVC release has been accompanied with various new contributions to improve the coding efficiency beyond the high-efficiency video coding (HEVC), particularly in the transformation process. The adaptive multiple transform (AMT) is one of the new tools that was introduced in the transform module. It involves five transform types from the...
In computed tomography (CT), scattering causes server quality degradation of the reconstructed CT images by introducing streaks and cupping artifacts which reduce the detectability of low contrast objects. Monte Carlo (MC) simulation is considered the most accurate approach for scatter estimation. However, the existing MC estimators are computationally expensive, especially for...
Light-field (LF) super-resolution (SR) plays an essential role in alleviating the current technology challenge in the acquisition of a 4D LF, which assembles both high-density angular and spatial information. Due to the algorithm complexity and data-intensive property of LF images, LFSR demands a significant computational effort and results in a long CPU processing time. This...
In recent years, object detection algorithms have achieved great success in the field of machine vision. To pursue the detection accuracy of the model, the scale of the network is constantly increasing, which leads to the continuous increase in computational cost and a large requirement for memory. The larger network scale allows their execution to take a longer time, facing the...
COVID-19 is a virus, which is transmitted through small droplets during speech, sneezing, coughing, and mostly by inhalation between individuals in close contact. The pandemic is still ongoing and causes people to have an acute respiratory infection which has resulted in many deaths. The risks of COVID-19 spread can be eliminated by avoiding physical contact among people. This...