A5101604498- Smart Agriculture and AI
- Remote Sensing in Agriculture
- Electrical and Bioimpedance Tomography
- Remote-Sensing Image Classification
- Plant-Microbe Interactions and Immunity
- Recommender Systems and Techniques
- Text and Document Classification Technologies
- Advanced Image Fusion Techniques
- Air Quality and Health Impacts
- Direction-of-Arrival Estimation Techniques
- Health and Well-being Studies
- Wildlife-Road Interactions and Conservation
- Flow Measurement and Analysis
- Plant Disease Management Techniques
- Spacecraft Design and Technology
- Land Use and Ecosystem Services
- Video Coding and Compression Technologies
- Neural Networks and Reservoir Computing
- Advanced Adaptive Filtering Techniques
- COVID-19 impact on air quality
- 3D Modeling in Geospatial Applications
- Sentiment Analysis and Opinion Mining
- Nematode management and characterization studies
- Image and Video Quality Assessment
- Climate variability and models
Hainan University
2024
Institute for Magnetospheric Physics
2024
Kyocera (United States)
2021
Halliburton (United States)
2018
The Ohio State University
2017
Pakistan Atomic Energy Commission
2005
Currently, the different deep neural network (DNN) learning approaches have done much for classification of hyperspectral images (HSIs), especially most them use convolutional (CNN). HSI data characteristics multidimensionality, correlation, nonlinearity, and a large amount data. Therefore, it is particularly important to extract deeper features in HSIs by reducing dimensionalities which help improve both spectral spatial domains. In this article, we present spatial–spectral algorithm, local...
The persistent increase in greenhouse gas (GHG) emissions, notably carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), since the mid-20th century has been a key driver of significant climate alterations. This study investigates complex feedback mechanisms that both influence are influenced by global dynamics, soil processes, GHG emissions. Our statistical approach incorporates correlation measures, highlighting limitations such analyses, namely their inability to confirm causality,...
Analysis of hyperspectral imagery (HSI) is a critical aspect remote sensing in precision agriculture, for which effective dimensionality reduction (DR) strategies the inherent complexity and uncertainty data are highly necessary. The fusion fuzzy logic with DR techniques offers potential promises to refine enough feature information from classification system, may potentially compromise information. However, graph-based deep learning, especially use graph attention networks (GATs), has...
With the increasing demand for multidimensional data processing, Geometric algebra (GA) has attracted more and attention in field of geographical information systems. GA unifies generalizes real numbers complex, quaternion, vector algebra, converts complicated relations operations into intuitive independent coordinate It also provides a solution solving processing with high correlation among dimensions avoids loss information. Traditional methods computer vision artificial intelligence (AI)...
With the increase of online businesses, recommendation algorithms are being researched a lot to facilitate process using existing information. Such multi-criteria (MCRS) helps end-users attain required results interest having different selective criteria – such as combinations implicit and explicit indicators in form ranking or rankings on matched dimensions. Current approaches typically use label correlation, by assuming that correlations shared all objects. In real-world tasks, however,...
Abnormal crops image data play crucial role in controlling crop diseases and pest for smart agriculture. However, current agricultural acquisition methods suffer from low-value data. This article presents a new strategy collect high-quality abnormal crops. First, novel Internet of Things (IoT) system is proposed, that integrates edge intelligence, motion–static synergy, which enables both coarse fine acquisition. To enhance efficiency value the IoT, this proposes an method based on...
This study examines the impact of COVID-19 pandemic on individuals' well-being, focusing interplay between income reduction, mental health, preventive measures, and overall happiness. Using an online survey 215 respondents, employs principal component analysis (PCA), structural equation modeling (SEM), descriptive statistics to analyze key relationships loss, precautions, The results reveal a significant negative correlation loss happiness, indicating that financial insecurity during...
Electrical capacitance tomography (ECT) exhibits several attractive features that are important for industrial process applications. These include low cost, high speed, and nonintrusive nature. However, due to its soft-field character, a relatively image resolution is an outstanding challenge ECT. While many efforts have been made tackle this by improvements in reconstruction algorithms, less has done enhance the basic ECT hardware sensor configuration data acquisition process. In paper, new...
With the advancement of networks and multimedia, digital watermarking technology has received worldwide attention as an effective method copyright protection. Improving anti-geometric attack ability algorithms using image feature-based have extensive attention. This paper proposes a novel robust algorithm based on SURF-DCT perceptual hashing (Speeded Up Robust Features Discrete Cosine Transform), namely blind watermarking. We design implement meaningful binary watermark embedding extraction...
Although Karachi city is one of the world's fastest growing cities and considered largest world, not much known about its roadside trees.The trees different types roads (e.g.Wide roads, Medium roads) in Sindhi, Pakistan were studied.Based on field sample survey, tree species diversity examined through indexes.Furthermore, relationship between above ground biomass biodiversity was studied by linear regression model.A total 180 plots surveyed, which divided into three main roads.The most...
After further review and discussions among the authors, we want to do experiment improve existing premature results. Specifically, authors add more complex analysis support Given importance of maintaining highest standards academic integrity, believe that withdrawal is most appropriate course action. All are fully aware this decision have agreed withdrawal. We had several rounds correspondence regarding matter, all been included in these communications ensure transparency prevent any...
Communication systems require fast and efficient adaptive channel equalization algorithms. In cyclostationarity based equalization, order is estimated by decomposing range space of an "overmodeled" data covariance matrix into signal noise subspaces. These methods are robust with respect to ratio, but computationally intensive leading slow convergence for large order. This paper proposes a method estimating on gap between subspaces; taking account the difference consecutive eigen values