搜索结果: 1-15 共查到“Deep Learning”相关记录71条 . 查询时间(0.062 秒)
Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States
LiDAR airborne laser scanning enhanced forest inventory aboveground biomass forest carbon deep learning Maine New Hampshire Vermont Massachusetts Connecticut Rhode Island
font style='font-size:12px;'>
2023/12/5
Light detection and ranging (LiDAR) has become a commonly-used tool for generating remotely-sensed forest inventories. However, LiDAR-derived forest inventories have remained uncommon at a regional sc...
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
font style='font-size:12px;'>
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...
Forest Farm Fire Drone Monitoring System Based on Deep Learning and Unmanned Aerial Vehicle Imagery
Forest Farm Fire Monitoring System Deep Learning
font style='font-size:12px;'>
2023/12/1
Forest fires represent one of the main problems threatening forest sustainability. Therefore, an early prevention system of forest fire is urgently needed. To address the problem of forest farm fire m...
On the Interplay Between Deep Learning and Dynamical Systems
Deep Learning Dynamical Systems 北大
font style='font-size:12px;'>
2023/6/16
The explosion of spatiotemporal data in the physical world requires new deep learning tools to model complex dynamical systems.
Deep-learning system explores materials’ interiors from the outside（图）
深度学习 材料内部 人工智能
font style='font-size:12px;'>
2023/6/6
Maybe you can’t tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from an airplane part to a medical implant. Their n...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Convergence and Implicit Regularization of Deep Learning Optimizers
深度学习 优化 收敛 隐式正则化
font style='font-size:12px;'>
2023/4/13
In this talk, I will present our recent work on the convergence/generalization analysis for the popular optimizers in deep learning. (1) We establish the convergence for Adam under (L0,L1 ) smoothness...
美国奥本大学Shiwen Mao教授来南京邮电大学通信与信息工程学院作“Deep Learning for WiFi-based Indoor Fingerprinting”专题报告（图）
美国 奥本大学 Shiwen Mao 深度学习 模型 信号 无线电地图
font style='font-size:12px;'>
2024/2/4
2023年3月24日上午，IEEE Fellow、美国奥本大学Shiwen Mao教授应邀来南京邮电大学通信与信息工程学院作“Deep Learning for WiFi-based Indoor Fingerprinting”专题报告。本次专题报告详细地介绍了室内定位的相关内容，为南京邮电大学通信与信息工程学院师生的相关科研工作开拓了新思路。本次报告由通信与信息工程学院周亮院长主持，学院逾三百名...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Real-time tool path planning using deep learning for subtractive manufacturing
深度学习 减材制造 实时刀具 路径规划
font style='font-size:12px;'>
2023/4/25
Tool path planning is a crucial factor of computer-aided design and manufacturing (CAD/CAM). To generate suitable tool paths, the previous methods often transform the problem into local or global opti...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Deep learning of multi-scale PDEs based on data generated from particle methods
粒子方法 数据 多尺度 偏微分方程 深度学习
font style='font-size:12px;'>
2023/4/26
Solving multi-scale PDEs is difficult in high-dimensional and/or convection-dominant cases. The interacting particle methods (IPM) are shown to outperform solving PDEs directly. Examples include compu...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Condensation in deep learning
深度学习 凝结 神经网络
font style='font-size:12px;'>
2023/4/28
Why do neural networks (NN) that look so complex usually generalize well? To understand this problem, we find some simple implicit regularizations during training NNs. The first is the frequency princ...
Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs（图）
GPU 流水线 大型图形 深度学习
font style='font-size:12px;'>
2023/6/20
Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy gri...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：A novel deep learning approach for tourism volume forecasting with tourist search data
游客搜索数据 旅游量预测 深度学习方法
font style='font-size:12px;'>
2023/5/8
Tourism volume forecasting is the hot topic in tourism management, and deep learning techniques as the promising tool are becoming popular for capturing the characteristics of tourism volume data, whi...
Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power ...
浙江大学光电科学与工程学院郝翔课题组论文《Spectral Imaging with Deep Learning》发表于《Light：Science & Applications》封面（图）
光谱成像 光学滤光片 光谱编码
font style='font-size:12px;'>
2023/3/10
2022年6月17日，浙江大学光电科学与工程学院郝翔课题组综述文章《Spectral imaging with deep learning》发表于《Light:Science&Applications》杂志第六期封面。该研究回顾了光谱成像技术应用深度学习的最新进展，对基于深度学习的光谱成像技术进行了梳理。研究对深度学习光谱成像的各种技术路线进行了原理阐述、研究总结，并整理了当前的光谱成像数据集、概...
Deep learning networks may prefer the human voice--as we do（图）
Deep learning networks prefer human voice
font style='font-size:12px;'>
2021/4/23
The digital revolution is built on a foundation of binaries, invisible 1s and 0s called bits. The notion that computers prefer to "speak" in binary numbers is rarely questioned. According to new resea...