Results 61 to 70 of about 52,085 (312)

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, Miaoning Ren, Sami Pekdemir, Mustafa Kalay, Nilgun Kayaci, Nail Gunaltay, Hakan Usta, Xian Huang, Mustafa Serdar Onses   +8 more
wiley   +1 more source

Analysis of comparative performance of deep learning models for sentiment analysis

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021
Sentiment analysis of text can be performed using machine learning and natural language processing methods. However, there is no single tool or method that is effective in all cases.
Mirza Murtaza
doaj   +1 more source

Waste Classification using Deep Learning Convolution Neural Nets

International Journal for Modern Trends in Science and Technology, 2020
The generation of waste India is becoming a great concern, and it has affected our environment and may even affect the life of people living near these dump sites. The recent study figures show that India generates nearly 26,000 MT of plastic waste on a daily basis and 94 lakh tonnes trash every year.
openaire   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

Initial condition based real time classification of power quality disturbance using deep convolution neural network with bidirectional long short‐term memory

IET Generation, Transmission & Distribution, 2023
The accurate classification of power quality disturbances (PQDs) is crucial for advancing real‐time monitoring and classification systems within the modern power grid.
Prabaakaran Kandasamy, Chandrasekaran Kumar, Muthuramalingam Lakshmanan, Selvaraj Jaisiva, Albert Alexander Stonier, Geno Peter, Vivekananda Ganji   +6 more
doaj   +1 more source

English Conversational Telephone Speech Recognition by Humans and Machines

, 2017
One of the most difficult speech recognition tasks is accurate recognition of human to human communication. Advances in deep learning over the last few years have produced major speech recognition improvements on the representative Switchboard ...
Audhkhasi, Kartik, Cui, Xiaodong, Dimitriadis, Dimitrios, Hall, Phil, Kurata, Gakuto, Lim, Lynn-Li, Picheny, Michael, Ramabhadran, Bhuvana, Roomi, Bergul, Saon, George, Sercu, Tom, Thomas, Samuel   +11 more
core   +1 more source

Using In Situ TEM to Understand the Surfaces of Electrocatalysts at Reaction Conditions: Single‐Atoms to Nanoparticles

Advanced Functional Materials, EarlyView.
This review summarizes recent advances in closed‐cell in situ TEM strategies for accurate determination of the activity and stability of single‐atom catalyst systems during operation. Operando conditions causing dynamic changes of SAC systems are highlighted and we explain why ensemble average‐based optical techniques may benefit from the technological
Martin Ek, Soshan Cheong, Julie Cairney, Richard D. Tilley, Ingemar Persson   +4 more
wiley   +1 more source

3sG: Three‐stage guidance for indoor human action recognition

IET Image Processing
Inference using skeleton to steer RGB videos is applicable to fine‐grained activities in indoor human action recognition (IHAR). However, existing methods that explore only spatial alignment are prone to bias, resulting in limited performance.
Hai Nan, Qilang Ye, Zitong Yu, Kang An
doaj   +1 more source

Point completion by a Stack‐Style Folding Network with multi‐scaled graphical features

IET Computer Vision, 2023
Point cloud completion is prevalent due to the insufficient results from current point cloud acquisition equipments, where a large number of point data failed to represent a relatively complete shape.
Yunbo Rao, Ping Xu, Shaoning Zeng, Jianping Gou   +3 more
doaj   +1 more source

CE-Dedup: Cost-Effective Convolutional Neural Nets Training based on Image Deduplication [PDF]

, 2021
Xuan Li, Liqiong Chang, Xue Liu
openalex   +1 more source