Results 41 to 50 of about 229,991 (273)
An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression
Sensors, 2023 Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo +6 more
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Structurally Colored Physically Unclonable Functions with Ultra‐Rich and Stable Encoding Capacity
Advanced Functional Materials, Volume 35, Issue 12, March 18, 2025.This study reports a design strategy for generating bright‐field resolvable physically unclonable functions with extremely rich encoding capacity coupled with outstanding thermal and chemical stability. The optical response emerges from thickness‐dependent structural color formation in ZnO features, which are fabricated by physical vapor deposition ...
Abidin Esidir +8 more
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Forest fire image recognition based on convolutional neural network
Journal of Algorithms & Computational Technology, 2019 In order to detect fire automatically, a forest fire image recognition method based on convolutional neural networks is proposed in this paper. There are two main types of fire recognition algorithms.
Yuanbin Wang, Langfei Dang, Jieying Ren
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Convolutional Neural Networks In Convolution
, 2018 Currently, increasingly deeper neural networks have been applied to improve their accuracy. In contrast, We propose a novel wider Convolutional Neural Networks (CNN) architecture, motivated by the Multi-column Deep Neural Networks and the Network In Network(NIN), aiming for higher accuracy without input data transmutation.
openaire +2 more sources
Recycling of Thermoplastics with Machine Learning: A Review
Advanced Functional Materials, EarlyView.This review shows how machine learning is revolutionizing mechanical, chemical, and biological pathways, overcoming traditional challenges and optimizing sorting, efficiency, and quality. It provides a detailed analysis of effective feature engineering strategies and establishes a forward‐looking research agenda for a truly circular thermoplastic ...
Rodrigo Q. Albuquerque +5 more
wiley +1 more source
Research on road extraction of remote sensing image based on convolutional neural network
EURASIP Journal on Image and Video Processing, 2019 Road is an important kind of basic geographic information. Road information extraction plays an important role in traffic management, urban planning, automatic vehicle navigation, and emergency management.
Yuantao Jiang
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Advanced Functional Materials, EarlyView.This study demonstrated single‐crystalline PbTiO3‐based memristors with atomically sharp interfaces, well‐ordered lattices, and minimal lattice mismatch. The devices exhibited an ON/OFF ratio exceeding 105, high stability, and rich resistance‐state modulation.
Haining Li +7 more
wiley +1 more source
INVESTIGATIONS ON THE POTENTIAL OF CONVOLUTIONAL NEURAL NETWORKS FOR VEHICLE CLASSIFICATION BASED ON RGB AND LIDAR DATA [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 In recent years, there has been a significant improvement in the detection, identification and classification of objects and images using Convolutional Neural Networks.
R. Niessner, H. Schilling, B. Jutzi
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Orthogonal Features Extraction Method and Its Application in Convolution Neural Network
Shanghai Jiaotong Daxue xuebao, 2021 In view of feature redundancy in the convolutional neural network, the concept of orthogonal vectors is introduced into features. Then, a method for orthogonal features extraction of convolutional neural network is proposed from the perspective of ...
LI Chen, LI Jianxun
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XCM: An Explainable Convolutional Neural Network for Multivariate Time Series Classification [PDF]
, 2021 Kevin Fauvel +4 more
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