Aiming at the problems of long operation time and poor flexibility of embedded processor, this paper proposes a structure of configurable execution unit based on RISC-v extended instruction set for computing granulari...
详细信息
Pancreatic cancer poses a significant challenge in early detection and treatment due to its malignant nature within the digestive tract. Recent studies, such as those conducted by the Pancreatic Cancer Action Network,...
详细信息
images captured in surveillance systems suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. We present a new image enhancement ...
详细信息
ISBN:
(纸本)9781510655546
images captured in surveillance systems suffer from low contrast and faint color. Recently, plenty of dehazing algorithms have been proposed to enhance visibility and restore color. We present a new image enhancement algorithm based on multi-scale block-rooting processing. The basic idea is to apply the frequency domain image enhancement approach for different image block scales. The parameter of transform coefficient enhancement for every block is driven through optimization of measure of enhancement. The main idea is that enhancing the contrast of an image would create more high-frequency content in the enhanced image than the original image. To test the performance of the proposed algorithm, the public database O-HAZE is used.
Implementing image dehazing and defogging on a Field Programmable Gate Array (FPGA) offers efficiency. Dehazing an image becomes particularly challenging in the presence of fog or haze. However, employing a dark chann...
详细信息
ISBN:
(数字)9798350382693
ISBN:
(纸本)9798350382709
Implementing image dehazing and defogging on a Field Programmable Gate Array (FPGA) offers efficiency. Dehazing an image becomes particularly challenging in the presence of fog or haze. However, employing a dark channel prior to dehazing allows the removal of haze particles from the image. Different modules are used in this process, such as Dynamic Atmospheric Light Estimation (DALE), Scene Recovery (SR), and Transmission Map Estimation (TME). The FPGA runs these modules in hardware and produces effective outcomes by employing imageprocessingalgorithms. In this case, using FPGA technology offers a number of benefits. The dehazing process can be accelerated by using FPGA's built-in parallel processing capabilities to execute numerous operations at once. Furthermore, FPGA implementations provide better throughput and reduced latency in comparison to conventional approaches, making them well-suited for real-time applications such as image dehazing and D
The paper deals with the analysis of the visual images obtained from fire detection systems. We review the existing approaches to the analysis of video surveillance data and propose a tool for data labeling and visual...
详细信息
This paper examines the progression and advancements in fault detection techniques for photovoltaic (Pv) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of Pv tech...
详细信息
This paper examines the progression and advancements in fault detection techniques for photovoltaic (Pv) panels, a target for optimizing the efficiency and longevity of solar energy systems. As the adoption of Pv technology grows, the need for effective fault detection strategies becomes increasingly paramount to maximize energy output and minimize operational downtimes of solar power systems. These approaches include the use of machine learning and deep learning methodologies to be able to detect the identified faults in Pv technology. Here, we delve into how machine learning models, specifically kernel-based extreme learning machines and support vector machines, trained on current-voltage characteristic (I-v curve) data, provide information on fault identification. We explore deep learning approaches by taking models like EfficientNet-B0, which looks at infrared images of solar panels to detect subtle defects not visible to the human eye. We highlight the utilization of advanced imageprocessing techniques and algorithms to exploit aerial imagery data, from Unmanned Aerial vehicles (UAvs), for inspecting large solar installations. Some other techniques like DeepLabv3 , Feature Pyramid Networks (FPN), and U-Net will be detailed as such tools enable effective segmentation and anomaly detection in aerial panel images. Finally, we discuss implications of these technologies on labor costs, fault detection precision, and sustainability of Pv installations.
Crossing the road is one of the major problems, due to the increase of fast-moving vehicles on the road. The challenges in the existing techniques utilized for traffic control can be overcome by using the Smart Traffi...
详细信息
In the process of plasma-electrolytic synthesis, a new physical surface is synthesized, consisting of a metal oxide layer of a modified surface and the synthesis of elements of a set of electrolyte plasma, the nodal s...
详细信息
ISBN:
(纸本)9781510655461
In the process of plasma-electrolytic synthesis, a new physical surface is synthesized, consisting of a metal oxide layer of a modified surface and the synthesis of elements of a set of electrolyte plasma, the nodal sources of the components of which are the components of the electrodes (electrolyte and metal surface). In this regard, the classification of plasma electro-discharge processes based on analyzing optical and electrical sensor data using machine learning methods is an actual task. It can be used for intelligent control algorithms of the sensor layers operations and conduct analytical and quantitative studies of the properties of nodal substances. The paper presents the experimental analysis of video and electrical parameters of the oxygen process, automated processing of the basic features of images of plasma-electrolyte discharges, and a segmentation approach of the electric-discharge machining. This approach can help create microsensor elements and materials and systems for intelligent modeling and launching of electrochemical methods for creating an electrolyte plasma and directed synthesis of substances. To test the performance of the proposed algorithm, the database STANKIN is used.
Within the paradigm of industry 5.0, manufacturing systems are seeking for human-centred production, where the operator finds high-level supervision tasks. In this context, low-level decision making should be performe...
详细信息
Within the paradigm of industry 5.0, manufacturing systems are seeking for human-centred production, where the operator finds high-level supervision tasks. In this context, low-level decision making should be performed by machines themselves. In this paper, a hybrid prognosis algorithm is developed to automatically inspect the cutting edges of drill-bits and to predict their Remaining Useful Life (RUL) and the associated probability density function. The solution relies on the automatic measurement of flank wear through convolutional filtering and edge detection. Prognosis exploits particle filter, which updates multi-layer perceptron with online data, to adaptively predict drill-bits RUL. The solution reduces the experimental preliminary run-to-failures needed for training standard machine learning algorithms, exploiting them in a real-time adaptive scenario, while predicting tool RUL under untested and variable cutting process operations. The algorithm uses direct wear observations, taken during set- up times (e.g., tool changes, workpiece change), thus not interfering with the process. (c) 2023 The Authors. Published by ELSEvIER B.v.
This article discusses various feature selection algorithms, namely SelectKBest with different statistical criteria and Random Forest algorithm, compares classification accuracy with and without feature selection algo...
详细信息
暂无评论