Pansharpening refers to the use of a panchromatic image to improve the spatial resolution of a multi-spectral image while preserving spectral signatures. However, existing pansharpening methods are still unsatisfactory at balancing the trade-off betw...
An increasing trend of moving towards single-stream waste management systems is occurring in many municipalities. This is because of the ability to process greater quantities of materials, minimize material management costs, and maximize recycling co...
Owing to their advantages over hard disc drives (HDDs), solid-state drives (SSDs) are widely used in many applications, including consumer electronics and data centers. As erase operations are feasible only in block units, modification or deletion of...
Write amplification factor (WAF) is a critical performance and endurance bottleneck in flash-based solid-state drives (SSDs). Multi-streamed SSDs mitigate WAF by enabling logical data streams to be written separately, thereby improving the efficiency...
In this paper, we leverage multimodal data to classify minerals using a multi-stream neural network. In a previous study on the Tinto dataset, which consisted of a 3D hyperspectral point cloud from the open-pit mine Corta Atalaya in Spain, we success...
Industrial water reuse and resource recovery are essential for advancing circular economy principles in water-intensive industries. Despite technological maturity, large-scale implementation continues to lag due to high costs, effluent variability, i...
Recently, with the widespread application of deep learning networks, appearance-based gaze estimation has made breakthrough progress. However, most methods focus on feature extraction from the facial region while neglecting the critical role of the e...
To comprehensively leverage the temporal, static, and dynamic information features of multi-channel surface electromyography (sEMG) signals for gesture recognition, considering the sensitive temporal characteristics of sEMG signals to action amplitud...
The 3-component velocity distribution of two lean-burn gas turbine fuel injectors are measured at a planar location near and parallel to the injector outlet. The two injectors are nominally the same design, but one features blocked central passages t...
Multi-stream graph convolutional networks improve skeleton action recognition by combining representations, but each branch adds inference cost. We evaluate one fixed stream-removal operating point in a CTR-GCN pipeline using a paired non-inferiority...
In action recognition research, two primary types of information are appearance and motion information that is learned from RGB images through visual sensors. However, depending on the action characteristics, contextual information, such as the exist...
Viscous liquid flow in micro-channels is typically laminar because of the low Reynolds number constraint. However, by introducing elasticity into the fluids, the flow behavior could change drastically to become turbulent; this elasticity can be reali...
Rice plays a pivotal role in global food security, particularly for Asian populations. However, its production is significantly threatened by insect pests, with Chilo suppressalis being a major pest in Asian rice-growing regions. Therefore, developin...
With the rapid advancement of image processing techniques, digital image forgery detection has emerged as a critical research area in information forensics. This paper proposes a novel deep learning model based on Multi-view Multi-dimensional Forgery...
This study examines differences in cost and recycling performance between single and multi-stream recycling systems in Ontario, Canada. Using panel data from 223 provincial municipalities spanning a ten year period, focus is placed on analyzing: (a)...
High-precision mapping of tree species composition is essential for sustainable forest management, biodiversity assessment, and ecosystem monitoring. Airborne hyperspectral imagery provides rich spectral and spatial information that enables detailed...
Accurate prediction of soybean yield is important for safeguarding food security and improving agricultural management. Recent advances have highlighted the effectiveness and ability of Machine Learning (ML) models in analyzing Remote Sensing (RS) da...
Hand Gesture Recognition (HGR) is a vital technology that enables intuitive human–computer interaction in various domains, including augmented reality, smart environments, and assistive systems. Achieving both high accuracy and real-time perfor...
Image deblurring has been a challenging ill-posed problem in computer vision. Gaussian blur is a common model for image and signal degradation. The deep learning-based deblurring methods have attracted much attention due to their advantages over the...
The global concern regarding the monitoring of construction workers’ activities necessitates an efficient means of continuous monitoring for timely action recognition at construction sites. This paper introduces a novel approach—the multi...
Unintentional human falls, particularly in older adults, can result in severe injuries and death, and negatively impact quality of life. The World Health Organization (WHO) states that falls are a significant public health issue and the primary cause...
Deepfake is one of the applications that is deemed harmful. Deepfakes are a sort of image or video manipulation in which a person’s image is changed or swapped with that of another person’s face using artificial neural networks. Deepfake manipulation...
Voice-activated artificial intelligence (AI) technology has advanced rapidly and is being adopted in various devices such as smart speakers and display products, which enable users to multitask without touching the devices. However, most devices equi...
Autonomous vehicles (AVs) rely heavily on multi-modal sensors to perceive their surroundings and make real-time decisions. However, the increasing complexity of these sensors, combined with the computational demands of AI models and the challenges of...
As a foundation and typical task in natural language processing, text classification has been widely applied in many fields. However, as the basis of text classification, most existing corpus are imbalanced and often result in the classifier tending...
Microbiome-based classification of multiple neurological conditions is challenged by sparse features, class imbalance, and heterogeneity between studies. We propose Multi-Stream Adaptive Feature Integration (MASFI), which combines CLR-transformed gen...
Recently, deep learning algorithms have been increasingly applied in construction for activity recognition, particularly for excavators, to automate processes and enhance safety and productivity through continuous monitoring of earthmoving activities...
Phonological-based features (articulatory features, AFs) describe the movements of the vocal organ which are shared across languages. This paper investigates a domain-adversarial neural network (DANN) to extract reliable AFs, and different multi-stre...
Deep learning has better detection efficiency than typical methods in photoelectric target detection. However, classical CNNs on GPU frameworks consume too much computing power and memory resources. We propose a multi-stream inference-optimized Tenso...
The organic rankine cycle (ORC) has been widely used to convert low-grade thermal energy to electricity. The selection of the cycle configuration, working fluid, and operating parameters is crucial for the economic profitability of the ORC system. In...
This study aims to provide an experimental investigation and comparison of the condensation heat transfer characteristics in a plate–fin heat exchanger (PFHE). The heat flux, mass flux, and saturation pressure were adjusted as experimental parameters...
The study investigates position-dependent variability in the slitting and rewinding process of filtration paper rolls under industrial conditions. Although individual cutting positions operate under identical machine settings, systematic differences...
This paper provides an overview of recent developments in quickest change detection (QCD) for high-dimensional multi-sensor systems, with an emphasis on settings involving structural constraints and limited sensing resources. Classical QCD methodolog...
Gesture spotting is an essential task for recognizing finger gestures used to control in-car touchless interfaces. Automated methods to achieve this task require to detect video segments where gestures are observed, to discard natural behaviors of us...
Various action recognition approaches have recently been proposed with the aid of three-dimensional (3D) convolution and a multiple stream structure. However, existing methods are sensitive to background and optical flow noise, which prevents from le...
Human falls, especially for elderly people, can cause serious injuries that might lead to permanent disability. Approximately 20–30% of the aged people in the United States who experienced fall accidents suffer from head trauma, injuries, or br...
We consider the problem of image set comparison, i.e., to determine whether two image sets show the same unique object (approximately) from the same viewpoints. Our proposition is to solve it by a multi-stream fusion of several image recognition path...
It is well known that aurorae have very high research value, but the data volume of aurora spectral data is very large, which brings great challenges to storage and transmission. To alleviate this problem, compression of aurora spectral data is indis...
The quality of feature extraction plays a significant role in the performance of speech emotion recognition. In order to extract discriminative, affect-salient features from speech signals and then improve the performance of speech emotion recognitio...
Numerous works have explored deep models for the classification of high-resolution natural images. However, limited investigation has been made into a deep classification for low-resolution synthetic aperture radar (SAR) images, which is a challengin...
This paper introduces a new analytical model of a multi-service system to which a heterogeneous mixture of stream, elastic, and adaptive traffic is offered, corresponding to data streams transmitted in real-world networks. The heterogeneity results f...
Sand and dust storm (SDS) weather has caused several severe hazards in many regions worldwide, e.g., environmental pollution, traffic disruptions, and human casualties. Widespread surveillance cameras show great potential for high spatiotemporal reso...
Vowel reduction is a common pronunciation phenomenon in stress-timed languages like English. Native speakers tend to weaken unstressed vowels into a schwa-like sound. It is an essential factor that makes the accent of language learners sound unnatura...
Aiming at the shortcomings of EEG emotion recognition models in feature representation granularity and spatiotemporal dependence modeling, a multimodal emotion recognition model integrating multi-scale feature representation and attention mechanism i...
Sign language recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. However, due to the complex background, light illumination, and subject structures in videos, researchers still face challe...
Despite the fact that automatic target recognition (ATR) in Synthetic aperture radar (SAR) images has been extensively researched due to its practical use in both military and civil applications, it remains an unsolved problem. The major challenges o...
Tracking objects across multiple video frames is a challenging task due to several difficult issues such as occlusions, background clutter, lighting as well as object and camera view-point variations, which directly affect the object detection. These...
Driver drowsiness is a major cause of fatal car accidents, and camera-based monitoring offers a promising way to detect it. Detecting drowsiness from video requires modeling both facial appearance and its temporal evolution. In this article, we propo...
Collisionless media devoid of intrinsic stresses, for example, a dispersed phase in a multiphase medium, have a much wider variety of space-time structures and features formed in them than collisional media, for example, a carrier, gas, or liquid pha...
The accurate identification of crop aphids is an important aspect of improving agricultural productivity. Aphids are characterised by small targets and a body colour similar to their surroundings. Even the most advanced detectors can experience probl...
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