A5102925116- Face and Expression Recognition
- Smart Agriculture and AI
- Spectroscopy and Chemometric Analyses
- Mathematical and Theoretical Epidemiology and Ecology Models
- Advanced Image and Video Retrieval Techniques
- Nonlinear Differential Equations Analysis
- Advanced Image Processing Techniques
- Matrix Theory and Algorithms
- Remote Sensing in Agriculture
- Mathematical Biology Tumor Growth
- Sparse and Compressive Sensing Techniques
- Semiconductor materials and devices
- Blind Source Separation Techniques
- Remote-Sensing Image Classification
- Generative Adversarial Networks and Image Synthesis
- Neural Networks Stability and Synchronization
- Advanced Computing and Algorithms
- IoT Networks and Protocols
- Nanowire Synthesis and Applications
- Fractional Differential Equations Solutions
- Electronic and Structural Properties of Oxides
- Video Surveillance and Tracking Methods
- Cancer Cells and Metastasis
- Semiconductor Quantum Structures and Devices
- Morphological variations and asymmetry
Agricultural Information Institute
2020-2024
Chinese Academy of Agricultural Sciences
2020-2023
Ministry of Agriculture and Rural Affairs
2022
Institute of Automation
2019
China University of Geosciences (Beijing)
2017
University of Electronic Science and Technology of China
2013-2016
Taiwan Semiconductor Manufacturing Company (Taiwan)
2006-2016
Nanjing University
2013-2015
The Synergetic Innovation Center for Advanced Materials
2015
Nanjing Tech University
2015
A periodic mathematical model of cancer treatment by radiotherapy is presented and studied in this paper. Conditions on the coexistence healthy cells are obtained. Furthermore, sufficient conditions existence globally asymptotic stability positive solution, eradication win solution established. Some numerical examples shown to verify validity results. discussion for further study.
Abstract Background Maize (Zea mays L.) is one of the most important food sources in world and has been main targets plant genetics phenotypic research for centuries. Observation analysis various morphological traits during maize growth are essential genetic breeding study. The generally huge number samples produce an enormous amount high-resolution image data. While high throughput phenotyping platforms increasingly used trials, there a reasonable need software tools that can automatically...
Training generative adversarial networks (GANs) for noise-to-image synthesis is a challenge task, primarily due to the instability of GANs’ training process. One key issues generator’s sensitivity input data, which can cause sudden fluctuations in loss value with certain inputs. This suggests an inadequate ability resist disturbances generator, causing discriminator’s oscillate and negatively impacting discriminator. Then, negative feedback discriminator also not conducive updating...
In <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0.53</sub> Ga xmlns:xlink="http://www.w3.org/1999/xlink">0.47</sub> As channel MOSFETs were fabricated on 300 mm Si substrate. The epitaxial layer exhibits high Hall electron mobility comparable to those grown lattice matched InP substrates. Excellent device characteristics (SS~95 mV/dec., I xmlns:xlink="http://www.w3.org/1999/xlink">on</sub> /I...
For the first time, we demonstrate smallest, fully functional 32Mb 6-T high density SRAM reported in literature with scaled bulk FinFETs for CMOS technology beyond 10nm node. Scaled FinFET devices exhibit excellent electrostatic DIBL of <45mV/V and sub-threshold swing <65mV/decade competitive drive current. Static noise margin ∼90mV operated down to 0.45V is achieved.
In recent years, semantic segmentation technology plays an important role in land resource management tasks. However, many classic methods often fail to obtain satisfactory results for remote sensing images with a large amount of interference information. order improve this situation, we propose Semantic Category Balance-Aware Involved Anti-Interference Network(SCBANet). SCBANet has encoder-decoder structure similar DeeplabV3+ [1]. On basis, Clustering Guided Decoupling Module(CGSDM),...
In order to better realize agricultural informatization, a data management system for supply chain, which has the characteristics of safe, credible, stable, traceable, information-sharing, and large-throughput, is needed construct. To date, information method China's chain usually stored in centralized database file system, with weak capabilities, leading problems such as theft, tampering, deletion, inconsistencies. light these problems, we introduce blockchain technology cutting-edge...
Message passing plays a vital role in graph neural networks (GNNs) for effective feature learning. However, the over-reliance on input topology diminishes efficacy of message and restricts ability GNNs. Despite efforts to mitigate reliance, existing study encounters message-passing bottlenecks or high computational expense problems, which invokes demands flexible with low complexity. In this paper, we propose novel dynamic mechanism It projects nodes learnable pseudo into common space...
Abstract With the rapid development of global IoT and various information technologies, construction “smart city” has been gradually put on agenda, at same time, smart management National Agricultural Science Technology Park will also become key content city construction. This paper proposes a scheme design platform for agricultural science technology park, lists basic contents park. The proposed applies 5G, AI, cloud computing, Internet Things, mobile other new ICT technologies to solve...
Abstract Background: Maize (Zea mays L.) is one of the most important food sources in world and has been main targets plant genetics phenotypic research for centuries. Observation analysis various morphological traits during maize growth are essential genetic breeding study. The generally huge number samples produce an enormous amount high-resolution image data. While high throughput phenotyping platforms increasingly used trials, there a reasonable need software tools that can automatically...
Designing effective graph neural networks (GNNs) with message passing has two fundamental challenges, i.e., determining optimal message-passing pathways and designing local aggregators. Previous methods of are limited information loss on the input features. On other hand, existing aggregators generally fail to extract multi-scale features approximate diverse operators under parameter scales. In contrast these methods, Euclidean convolution been proven as an expressive aggregator, making it a...
We study a two-patch impulsive migration periodic<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>N</mml:mi></mml:mrow></mml:math>-species Lotka-Volterra competitive system. Based on analysis method, inequality estimation, and Lyapunov function sufficient conditions for the permanence existence of unique globally stable positive periodic solution system are established. Some numerical examples shown to verify our results discuss model further.
A novel approach based on low‐rank representations (LRRs) for image is proposed. LRR seeks the lowest‐rank among all coefficient matrices that represent images as linear combinations of basis in given dictionary. Unlike methods enforcing additional constraints representation and dictionary, an iterative process which decomposition performed has been developed. The rank will be lower with iterations, termed deep (DLR) method. Extensive experiments were conducted to verify state‐of‐the‐art...
Abstract The Internet of Things (IoT) requires different but complementary types wireless network technologies, having their own merits from distance, power consumption, capacity and cost perspectives. This paper introduces a comparative study LoRa communication technology for the long-distance low-power wide-area scenario deployment. In this paper, we propose construction method based on an agricultural science park in Ningxia, Western China. Specifically, design optimal placement sensors...
Nonnegative matrix factorization (NMF) is a useful tool in learning basic representation of image data. However, its performance and applicability real scenarios are limited because the lack information. In this paper, we propose constrained decomposition algorithm for which contains parameters associated with characteristics data sets. Particularly, impose label information as additional hard constraints to α -divergence-NMF unsupervised algorithm. The resulted derived by using...