The effectiveness of deep learning in completing tasks comprehensively has led to a rapid increase in its usage. Deep learning encompasses numerous diverse methods, each with its own distinct characteristics. The aim of this study is to synthesize existing literature in order to classify and...

This study proposes integrated image processing and deep learning approaches for wheat rust disease detection and grading. Wheat stripe rust is one of the diseases affecting the crop in nearly all wheat-growing countries, where humidity and high temperatures characterize the growing season. The...

Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirement years, mostly betting on stocks or indexes...

Stock trading has tremendous importance not just as a profession but also as an income source for individuals. Many investment account holders use the appreciation of their portfolio (as a combination of stocks or indexes) as income for their retirement years, mostly betting on stocks or indexes...

Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-poor regions, yet the resource requirements of SIML limit its accessibility and use. We show that a single encoding of...

Purpose While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load...

An iterative technique for the removal of artifacts caused by the near field effects of a coded aperture imaging system is presented. The technique, we we call z-Clean, first locates high energy sources within a three dimensional field of view using a least squares method and then removes the...

Combining satellite imagery with machine learning (SIML) has the potential to address global challenges by remotely estimating socioeconomic and environmental conditions in data-poor regions, yet the resource requirements of SIML limit its accessibility and use. We show that a single encoding of...

Diese Studie befasst sich mit den Auswirkungen des Einsatzes von Gesichtserkennungssoftware im stationären Einzelhandel. Das zentrale Forschungsthema ist die Frage, inwieweit das Wissen des Kunden über den Einsatz von Gesichtserkennungssoftware im stationären Einzelhandel seine...

Purpose Hundreds of thousands of deaths each year in the world are caused by breast cancer (BC). An early-stage diagnosis of this disease can positively reduce the morbidity and mortality rate by helping to select the most appropriate treatment options, especially by using histological BC images...

Purpose To improve production efficiency, industrial robots are expected to replace humans to complete the traditional manual operation on grasping, sorting and assembling workpieces. These implementations are closely related to the accuracy of workpiece location. However, workpiece location...

Purpose Visual object tracking plays a significant role in intelligent robot systems. This study aims to focus on unlocking the tracking performance potential of the deep network and presenting a dynamic template update strategy for the Siamese trackers. Design/methodology/approach This paper...

Purpose In novelty detection, the autoencoder based image reconstruction strategy is one of the mainstream solutions. The basic idea is that once the autoencoder is trained on normal data, it has a low reconstruction error on normal data. However, when faced with complex natural images, the...

Purpose Focusing on the problem that the visual detection algorithm of navigation path line in intelligent harvester robot is susceptible to interference and low accuracy, a navigation path detection algorithm based on improved random sampling consensus is proposed. Design/methodology/approach...

Purpose This paper aims to present a natural human–robot teleoperation system, which capitalizes on the latest advancements of monocular human pose estimation to simplify scenario requirements on heterogeneous robot arm teleoperation. Design/methodology/approach Several optimizations in the...

Purpose Accurately, positioning is a fundamental requirement for vision measurement systems. The calculation of the harvesting width can not only help farmers adjust the direction of the intelligent harvesting robot in time but also provide data support for future unmanned vehicles....

This work describes a relatively simple yet effective method for analyzing harmonic distortions and spectral analysis of electronic signals up to the MHz range. The method involves the use a suitable analog or digital oscilloscopes to present the signal, taking a digital picture of the...

Automated guided vehicles’ application in production facilities increases continuously. As these vehicles count as the industrialized version of mobile robots, the later ones can be regarded as the future of industrial AGVs. One of the most important issue of mobile robots is sensors....

Automated guided vehicles’ application in production facilities increases continuously. As these vehicles count as the industrialized version of mobile robots, the later ones can be regarded as the future of industrial AGVs. One of the most important issue of mobile robots is sensors....

Gathering and examining progressively multi-modular sensor information of human faces is a critical issue in PC vision, with applications in examinations, entertainment, and security. However, due to the exigent nature of the problem, there is a lack of affordable and easy-to-use systems, with...

This article describes how robust image processing application rely heavily on image descriptors extracted. Limited work is carried out in adopting probabilistic finite state automata (PFSA) models for image processing. A finite state automata for image processing (FSAFIP) method is presented...

The article proposes an image processing-based automatic methodology for early diagnosis of colorectal cancer. In pathology, staining and sectioning of tissues are routinely used as a primary technique to detect cancer. In this methodology, the colorectal gland tissues are segmented by using...

Schistosomiasis is serious liver tissues' parasitic disease that leads to liver fibrosis. Microscopic liver tissue images at different stages can be used for assessment of the fibrosis level. In the current article, the different stages of granuloma were classified after features extraction....

Face recognition is considered as one of toughest and most crucial leading domains of digital image processing. The human brain also uses a similar kind of technique for face recognition. When scrutinizing a face, the human brain signifies the result. Aside from AN automatic processing system,...