A5100781351- Smart Agriculture and AI
- Infrared Target Detection Methodologies
- Advanced Semiconductor Detectors and Materials
- Plant Disease Management Techniques
- Advanced Image and Video Retrieval Techniques
- Thermography and Photoacoustic Techniques
- Plant Virus Research Studies
- Robotics and Sensor-Based Localization
- Luminescence Properties of Advanced Materials
- Chemical Thermodynamics and Molecular Structure
- Speech and Audio Processing
- Anomaly Detection Techniques and Applications
- Food Supply Chain Traceability
- Music and Audio Processing
- Energetic Materials and Combustion
- Music Technology and Sound Studies
- Cloud Computing and Resource Management
- Solid-state spectroscopy and crystallography
- Traffic Prediction and Management Techniques
- Crystallography and molecular interactions
- Gait Recognition and Analysis
- Inorganic Fluorides and Related Compounds
- Advanced Decision-Making Techniques
- Technology and Security Systems
- Remote-Sensing Image Classification
Anhui University of Science and Technology
2025
China Agricultural University
2024-2025
Beijing University of Technology
2024-2025
Shenyang Jianzhu University
2023-2024
HoF
The rapid advancement in smart agriculture has introduced significant challenges, including data scarcity, complex and diverse disease features, substantial background interference agricultural scenarios. To address these a detection method based on few-shot learning diffusion generative models is proposed. By integrating the high-quality feature generation capabilities of with extraction advantages learning, an end-to-end framework for been constructed. experimental results demonstrate that...
This paper proposes a disease detection model based on the maxmin-diffusion mechanism, aimed at improving accuracy and robustness of tasks in agricultural field. With development smart agriculture, automated has become one key driving modernization. Traditional models often suffer from significant loss issues when dealing with complex types dynamically changing time-series data. To address these problems, this introduces which adjusts attention weights to enhance model’s focus regions while...
The development of smart agriculture has created an urgent demand for efficient and accurate weed recognition detection technologies. However, the diverse complex morphology weeds, coupled with scarcity labeled data in agricultural scenarios, poses significant challenges to traditional supervised learning methods. To address these issues, a model based on semi-supervised diffusion generative network is proposed. This integrates attention mechanism semi-diffusion loss enable utilization both...
This study presents the results of high-pressure Raman and angle-dispersive X-ray diffraction (ADXRD) investigations conducted on hexamethylenetetramine (HMT, (CH2)6N4), a hydrogen-bonded pharmaceutical energetic material, across range pressures up to approximately 20 GPa. Notably, two distinct phase transitions at around 1.1 GPa within pressure interval 10 12.5 were identified. Both spectroscopy ADXRD substantiate existence these transitions. The crystal structure II could be indexed...
Synthesizer is a type of electronic musical instrument that now widely used in modern music production and sound design. Each parameters configuration synthesizer produces unique timbre can be viewed as instrument. The problem estimating set best restore an important yet complicated problem, i.e.: the estimation problem. We proposed multi-modal deep-learning-based pipeline Sound2Synth, together with network structure Prime-Dilated Convolution (PDC) specially designed to solve this Our method...
Infrared Small Target Detection is a challenging task to separate small targets from infrared clutter background. Recently, deep learning paradigms have achieved promising results. However, these data-driven methods need plenty of manual annotations. Due the size targets, annotation consumes more resources and restricts development this field. This letter proposed labor-efficient framework with level set, which obtains high-quality pseudo mask only one cursory click. A variational set...
This study aims to improve the precision of wheat spike counting and disease detection, exploring application deep learning in agricultural sector. Addressing shortcomings traditional detection methods, we propose an advanced feature extraction strategy a model based on probability density attention mechanism, designed more effectively handle complex backgrounds dense areas. Through comparative experiments with various models, comprehensively evaluate performance our model. In task, performs...
Infrared Small Target Detection is a challenging task to separate small targets from infrared clutter background. Recently, deep learning paradigms have achieved promising results. However, these data-driven methods need plenty of manual annotation. Due the size targets, annotation consumes more resources and restricts development this field. This letter proposed labor-efficient cursory framework with level set, which obtains high-quality pseudo mask only one click. A variational set...
In this paper, we introduce the first Challenge on Multi-modal Aerial View Object Classification (MAVOC) in conjunction with NTIRE 2021 workshop at CVPR. This challenge is composed of two different tracks using EO andSAR imagery. Both and SAR sensors possess advantages drawbacks. The purpose competition to analyze how use both sets sensory information complementary ways. We discuss top methods submitted for evaluate their results our blind test set. Our show significant improvement more than...