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中国科学院半导体研究所高速电路与神经网络实验室刘婧逸博士一篇论文被人工智能顶刊Neural Networks录用（图）
中国科学院 高速电路 神经网络 刘婧逸 人工智能 Neural Networks
2023/7/11
近日，实验室2021级博士研究生刘婧逸的学术论文《SNR: Symbolic Network-based Rectifiable Learning Framework for Symbolic Regression》被人工智能顶级期刊Neural Networks录用。《Neural Networks》是世界上三个最古老的神经建模学会的档案期刊:国际神经网络学会(INNS)、欧洲神经网络学会(EN...
Cornell researchers have developed an optical neural network (ONN) that can filter relevant information from a scene before the visual image is detected by a camera, a method that may make it possible...
In the vast, expansive skies where birds once ruled supreme, a new crop of aviators is taking flight. These pioneers of the air are not living creatures, but rather a product of deliberate innovation:...
A method for designing neural networks optimally suited for certain tasks（图）
神经网络 机器学习模型 计算机网络
2023/3/30
Neural networks, a type of machine-learning model, are being used to help humans complete a wide variety of tasks, from predicting if someone’s credit score is high enough to qualify for a loan to dia...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Implicit biases of optimization algorithms for neural networks and their effects on generalization
神经网络 优化算法 隐式偏差 泛化的影响
2022/12/23
Modern neural networks are usually over-parameterized—the number of parameters exceeds the number of training data. In this case the loss functions tend to have many (or even infinite) global minima, ...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Calculation of high-order harmonic generation of atoms and molecules by combining time series prediction and neural networks
时间序列预测 神经网络计算 原子分子 高阶谐波生成
2022/11/17
High-order harmonic generation (HHG) from the interaction of ultra-intense laser pulses with atoms is an important tabletop short-wave coherent light source. Accurate quantum simulations of it present...
Many of us easily recognize emotions expressed in others’ faces. A smile may mean happiness, while a frown may indicate anger. Autistic people often have a more difficult time with this task. It’s unc...
西南交通大学电气工程学院刘志刚教授担任国际期刊IEEE Transactions on Neural Networks and Learning Systems (IF: 11.683)的Associate Editor
西南交通大学 电气工程学院 刘志刚 教授 国际期刊 IEEE Transactions on Neural Networks and Learning Systems
2019/12/2
日前，我院刘志刚教授应邀担任国际权威学术期刊IEEE Transactions on Neural Networks and Learning Systems (TNLLS) 的Associate Editor (副主编或编委)。2018年TNLLS最新的影响因子为 11.683，在计算机科学的理论与方法领域排名第一，在计算机科学的人工智能领域排名第二，在计算机科学的电气电子工程领域排名第三。TN...
VAULT MODELING WITH NEURAL NETWORKS
Automation Machine learning Modeling Neural Network Point cloud Vault
2019/3/1
Nowadays, the digital reconstruction of vaults is carried out using photogrammetric and laser scanning techniques able to capture the visible surface with dense point clouds. Then, different modeling ...
CLASSIFICATION OF THE STRUCTURE OF CITIES THROUGH MID-RESOLUTION SATELLITE IMAGERY AND PATCH BASED NEURAL NETWORKS
Convolutional Neural Networks (CNN) Autoencoders Sentinel 2B Indian Cities
2018/11/19
The studies in the classification of the urban spatial structure have been essential in deriving insights into the land cover and the built typology which helped in the estimation of energy consumptio...
Prediction of the effectiveness of rolling dynamic compaction using artificial neural networks and cone penetration test data
soil mechanics rolling dynamic compaction artificial neural networks cone penetration test ground improvement
2018/9/7
Rolling Dynamic Compaction (RDC)，which is a ground improvement technique involving non-circular modules drawn behind a tractor，has provided the construction industry with an improved ground compaction...
EXTRACTION OF BUILT-UP AREAS USING CONVOLUTIONAL NEURAL NETWORKS AND TRANSFER LEARNING FROM SENTINEL-2 SATELLITE IMAGES
Built-up Area Extraction Convolutional Neural Networks Deep Learning Sentinel-2 Images Transfer Learning
2018/4/30
With rapid globalization, the extent of built-up areas is continuously increasing. Extraction of features for classifying built-up areas that are more robust and abstract is a leading research topic f...
SOIL MOISTURE RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS: APPLICATION TO PASSIVE MICROWAVE REMOTE SENSING
Soil Moisture Retrieval Microwave Remote Sensing Deep Learning Convolutional Neural networks GPU
2018/4/30
A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role ...
ETALON IMAGES: UNDERSTANDING THE CONVOLUTION NEURAL NETWORKS
CNN deep learning manifold learning affine transformations graphs etalons
2018/3/30
In this paper we propose a new technic called etalons, which allows us to interpret the way how convolution network makes its predictions. This mechanism is very similar to voting among different expe...
Following the successes of previous events, the 15th International Symposium on Neural Networks (ISNN 2018) will be held in Minsk, Belarus. Located by the Svislach and the Nyamiha Rivers, Minsk is the...