Results 81 to 90 of about 1,980,897 (317)

Non‐stationary financial time series forecasting based on meta‐learning

Electronics Letters, 2023
In this letter, the authors address the challenge in forecasting non‐stationary financial time series by proposing a meta‐learning based forecasting model equipped with a convolution neural network (CNN) predictor and a long short‐term memory (LSTM) meta‐
Anqi Hong, Minghan Gao, Qiang Gao, Xiao‐Hong Peng   +3 more
doaj   +1 more source

Learning shape correspondence with anisotropic convolutional neural networks [PDF]

, 2016
Convolutional neural networks have achieved extraordinary results in many computer vision and pattern recognition applications; however, their adoption in the computer graphics and geometry processing communities is limited due to the non-Euclidean ...
Rodolà, Emanuele, Bronstein, Michael, Masci, Jonathan, Boscaini, Davide, Bronstein, Michael M.   +4 more
core  

DeepID-Net: Deformable deep convolutional neural networks for object detection [PDF]

2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has innovations in multiple aspects. In the proposed new deep architecture, a new deformation constrained pooling (def-pooling) layer models the deformation of object parts with geometric constraint and
Wanli Ouyang, Xiaogang Wang 0001, Xingyu Zeng, Shi Qiu, Ping Luo 0002, Yonglong Tian, Hongsheng Li 0001, Shuo Yang 0003, Zhe Wang 0006, Chen Change Loy, Xiaoou Tang   +10 more
openaire   +4 more sources

Bioinspired Adaptive Sensors: A Review on Current Developments in Theory and Application

Advanced Materials, EarlyView.
This review comprehensively summarizes the recent progress in the design and fabrication of sensory‐adaptation‐inspired devices and highlights their valuable applications in electronic skin, wearable electronics, and machine vision. The existing challenges and future directions are addressed in aspects such as device performance optimization ...
Guodong Gong, You Zhou, Qingxiu Li, Wenyu Zhao, Sunyingyue Geng, Hangfei Li, Yan‐Bing Leng, Shirui Zhu, Guanglong Ding, Yongbiao Zhai, Ziyu Lv, Ye Zhou, Su‐Ting Han   +12 more
wiley   +1 more source

Lightweight attention‐guided redundancy‐reuse network for real‐time semantic segmentation

IET Image Processing, 2023
Semantic segmentation is a critical topic in computer vision, and it has numerous practical applications, including mobile devices, autonomous driving, and many other fields.
Xuegang Hu, Shuhan Xu, Liyuan Jing
doaj   +1 more source

Y-Net: A deep Convolutional Neural Network for Polyp Detection

CoRR, 2018
Colorectal polyps are important precursors to colon cancer, the third most common cause of cancer mortality for both men and women. It is a disease where early detection is of crucial importance. Colonoscopy is commonly used for early detection of cancer and precancerous pathology.
Ahmed Kedir Mohammed, Sule Yildirim, Ivar Farup, Marius Pedersen, Øistein Hovde   +4 more
openaire   +4 more sources

Deep deformable registration: Enhancing accuracy by fully convolutional neural net [PDF]

Pattern Recognition Letters, 2017
Deformable registration is ubiquitous in medical image analysis. Many deformable registration methods minimize sum of squared difference (SSD) as the registration cost with respect to deformable model parameters. In this work, we construct a tight upper bound of the SSD registration cost by using a fully convolutional neural network (FCNN) in the ...
Sayan Ghosal, Nilanjan Ray
openaire   +3 more sources

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

Advanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

Astronomical object recognition by means of neural networks

, 1998
Astronomical wide field imaging deals with Terabytes data sets and requires new strategies for data reduction and analysis. We discuss here the application of different types of neural nets to the detection and extraction of celestial objects ...
Andreon S., Longo G., Tagliaferri R., Zaggia S., Gargiulo G., Capuano N.   +5 more
core   +1 more source

Data‐driven target localization using adaptive radar processing and convolutional neural networks

IET Radar, Sonar & Navigation
Leveraging the advanced functionalities of modern radio frequency (RF) modeling and simulation tools, specifically designed for adaptive radar processing applications, this paper presents a data‐driven approach to improve accuracy in radar target ...
Shyam Venkatasubramanian, Sandeep Gogineni, Bosung Kang, Ali Pezeshki, Muralidhar Rangaswamy, Vahid Tarokh   +5 more
doaj   +1 more source