Results 11 to 20 of about 494,722 (259)

Learning multi-scale features for foreground segmentation [PDF]

Pattern Analysis and Applications, 2019
Foreground segmentation algorithms aim segmenting moving objects from the background in a robust way under various challenging scenarios. Encoder-decoder type deep neural networks that are used in this domain recently perform impressive segmentation results.
Long Ang Lim, Hacer Yalim Keles
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Multi-scale phase-based local features [PDF]

2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings., 2003
Local feature methods suitable for image feature based object recognition and for the estimation of motion and structure are composed of two steps, namely the 'where' and 'what' steps. The 'where' step (e.g., interest point detector) must select image points that are robustly localizable under common image deformations and whose neighborhoods are ...
Gustavo Carneiro 0001, Allan D. Jepson
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Automatic analysis framework based on 3D-CT multi-scale features for accurate prediction of Ki67 expression levels in substantial renal cell carcinoma

Insights into Imaging, 2023
Purpose To investigate the effectiveness of an automatic analysis framework based on 3D-CT multi-scale features in predicting Ki67 expression levels in substantial renal cell carcinoma (RCC).
Huancheng Yang, Jiashan Lin, Hanlin Liu, Jiehua Yao, Qianyu Lin, Jiaxin Wang, Feiye Jiang, Liying Wei, Chongyang Lin, Kai Wu, Song Wu   +10 more
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Multi-scale Feature Aggregation for Crowd Counting

CoRR, 2022
Convolutional Neural Network (CNN) based crowd counting methods have achieved promising results in the past few years. However, the scale variation problem is still a huge challenge for accurate count estimation. In this paper, we propose a multi-scale feature aggregation network (MSFANet) that can alleviate this problem to some extent.
Xiaoheng Jiang, Xinyi Wu, Hisham Cholakkal, Rao Muhammad Anwer, Jiale Cao, Mingliang Xu 0001, Bing Zhou 0003, Yanwei Pang, Fahad Shahbaz Khan   +8 more
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A Few Shot Classification Methods Based on Multiscale Relational Networks

Applied Sciences, 2022
Learning information from a single or a few samples is called few-shot learning. This learning method will solve deep learning’s dependence on a large sample. Deep learning achieves few-shot learning through meta-learning: “how to learn by using previous
Wenfeng Zheng, Xia Tian, Bo Yang, Shan Liu, Yueming Ding, Jiawei Tian, Lirong Yin   +6 more
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A Novel 2D-3D CNN with Spectral-Spatial Multi-Scale Feature Fusion for Hyperspectral Image Classification

Remote Sensing, 2021
Multifarious hyperspectral image (HSI) classification methods based on convolutional neural networks (CNN) have been gradually proposed and achieve a promising classification performance.
Dongxu Liu, Guangliang Han, Peixun Liu, Hang Yang, Xinglong Sun, Qingqing Li, Jiajia Wu   +6 more
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Evaluating Precipitation Features and Rainfall Characteristics in a Multi‐Scale Modeling Framework

Journal of Advances in Modeling Earth Systems, 2020
Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product.
Jiun‐Dar Chern, Wei‐Kuo Tao, Stephen E. Lang, Xiaowen Li, Toshihisa Matsui   +4 more
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CLOUD DETECTION BY FUSING MULTI-SCALE CONVOLUTIONAL FEATURES [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018
Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks.
Z. Li, H. Shen, H. Shen, Y. Wei, Q. Cheng, Q. Yuan, Q. Yuan   +6 more
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SSD with multi-scale feature fusion and attention mechanism

Scientific Reports, 2022
Abstract In the field of the Internet of Things, image acquisition equipment is the very important equipment, which will generate lots of invalid data during real-time monitoring. Analyzing the data collected directly from the terminal by edge calculation, we can remove invalid frames and improve the accuracy of system detection.
Qiang Liu, Lijun Dong, Zhigao Zeng, Wenqiu Zhu, Yanhui Zhu, Chen Meng   +5 more
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Chinese Sentiment Analysis Based on CNN-BiLSTM Model of Multi-level and Multi-scale Feature Extraction [PDF]

Jisuanji kexue, 2023
Sentiment analysis,as a sub-field of natural language processing(NLP),plays a very important role in public opinion monitoring.In the Chinese sentiment analysis task,the existing methods only consider sentiment features from single-level and single-scale,
WANG Lin, MENG Zuqiang, YANG Lina
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