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Evaluation of conditioned Latin hypercube sampling for soil mapping based on a machine learning method
Conditioned Latin hypercube sampling Soil mapping Representativeness Sample randomness
2024/1/12
Sampling design plays an important role in soil survey and soil mapping. Conditioned Latin hypercube sampling (cLHS) has been proven as an efficient sampling strategy and used widely in digital soil m...
Wheat Lodging Detection from UAS Imagery Using Machine Learning Algorithms
precision agriculture field crops machine learning deep learning image processing textural features
2023/12/21
The current mainstream approach of using manual measurements and visual inspections for crop lodging detection is inefficient, time-consuming, and subjective. An innovative method for wheat lodging de...
Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms-Case Study of Evergreen Conifer Planted Forests in Japan
UAS stem volume TLS SAR random forest support vector multiple regression forest biophysical parameter
2023/12/21
The development of new methods for estimating precise forest structure parameters is essential for the quantitative evaluation of forest resources. Conventional use of satellite image data, increasing...
Ensemble machine-learning-based framework for estimating total nitrogen concentration in water using drone-borne hyperspectral imagery of emergent plants: A case study in an arid oasis, NW China
Water resources Remote sensing Total nitrogen Hyperspectral imagery Machine learning Bootstrap
2023/12/19
In arid and semi-arid regions, water-quality problems are crucial to local social demand and human well-being. However, the conventional remote sensing-based direct detection of water quality paramete...
Semi-Automated Semantic Segmentation of Arctic Shorelines Using Very High-Resolution Airborne Imagery, Spectral Indices and Weakly Supervised Machine Learning Approaches
land water segmentation remote sensing deep learning sparse labels
2023/12/5
Precise coastal shoreline mapping is essential for monitoring changes in erosion rates, surface hydrology, and ecosystem structure and function. Monitoring water bodies in the Arctic National Wildlife...
Climate-Based Regionalization and Inclusion of Spectral Indices for Enhancing Transboundary Land-Use/Cover Classification Using Deep Learning and Machine Learning
machine learning ratio-based indices orthogonal indices Koppen–Geiger climate regionalization landscape change remote sensing landcover
2023/12/4
Accurate land use and cover data are essential for effective land-use planning, hydrological modeling, and policy development. Since the Okavango Delta is a transboundary Ramsar site, managing natural...
Wildfire Risk Assessment in Liangshan Prefecture, China Based on An Integration Machine Learning Algorithm
frequency ratio MCD64A1 Bayesian optimization support vector machine random forest extreme gradient boosting
2023/11/30
Previous wildfire risk assessments have problems such as subjectivity of weight allocation and the linearization of statistical models, resulting in generally low robustness and low generalization abi...
苏州大学计算机科学与技术学院杨壮老师的论文在机器学习顶级期刊Journal of Machine Learning Research （JMLR）上在线发表（图）
杨壮 机器学习 Journal of Machine Learning Research
2024/2/3
苏州大学计算机科学与技术学院杨壮副教授撰写的论文“Improved Powered Stochastic Optimization Algorithms for Large-Scale Machine Learning”在机器学习顶级期刊Journal of Machine Learning Research（JMLR）上在线发表，杨壮副教授为该论文的唯一作者，苏州大学计算机科学与技术学院为该论文...
Machine learning-based atom contribution method for the prediction of surface charge density profiles and solvent design
atom contribution computer-aided molecular design decomposition-based algorithm machine learning
2023/6/19
Solvents are widely used in chemical processes. The use of efficient model-based solvent selection techniques is an option worth considering for rapid identification of candidates with better economic...
南京农业大学农学院《Plant Physiology》发表黄骥教授“RiceTFtarget: A Rice Transcription Factor-Target Prediction Server Based on Co-expression and Machine Learning”（图）
黄骥 基因 生物信息学 作物
2023/10/28
转录因子（TF）在基因表达调控中发挥了重要作用。鉴定转录因子的靶基因或与靶基因启动子结合的转录因子对于解析转录因子-靶基因模块的生物学功能和调控网络至关重要。2023年6月15日，作物生物信息学课题组在Plant Physiology发表了题为“RiceTFtarget: A Rice Transcription Factor-Target Prediction Server Based on C...
Why is machine learning trending in medical research but not in our doctor’s offices?（图）
Bioengineering Penn Integrates Knowledge Professors Computer Science
2023/6/27
Machine learning (ML) programs computers to learn the way we do—through the continual assessment of data and identification of patterns based on past outcomes. ML can quickly pick out trends in big da...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Machine learning methods for forward and inverse PDEs
正反向 偏微分方程 机器学习
2023/4/27
本报告介绍我们近期的两项工作。(1) 求解PDE的PINN方法在处理时间发展方程时往往遇到难以收敛的困难。我们发展了时间方向的预训练PINN方法及自适应步长方法，解决了收敛性困难，使PDE求解精度能够得到系统性提高。我们在一系列时间发展方程上获得了比文献报道更精确的训练结果。(2) 辐射调源问题是一个典型的反问题，要求调整辐射输运方程的边条件(源)，使解满足特定设计目标。我们针对辐射输运方程的时序...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Towards Provably Efficient Quantum Algorithms for Nonlinear Dynamics and Large-scale Machine Learning Models
非线性动力学 机器学习模型 高效量子算法
2023/4/13
Nonlinear dynamics play a prominent role in many domains and are notoriously difficult to solve. Whereas previous quantum algorithms for general nonlinear equations have been severely limited due to t...
It’s no secret that OpenAI’s ChatGPT has some incredible capabilities — for instance, the chatbot can write poetry that resembles Shakespearean sonnets or debug code for a computer program. These abil...
南京农业大学农学院《Science of The Total Environment》发表智慧农业团队“Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed winter wheat cropland”（图）
智慧农业 碳循环 生态系统
2023/10/28
2023年2月25日，农学院智慧农业团队在《Science of The Total Environment》期刊发表了题为“Improving the spatial and temporal estimation of ecosystem respiration using multi-source data and machine learning methods in a rainfed ...