Results 61 to 70 of about 102,874 (306)

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Video‐based action recognition using spurious‐3D residual attention networks

IET Image Processing, 2022
Recently, 3D Convolutional Neural Networks (3D CNNs) have attracted extensive attention in extracting spatial and temporal features in videos for their efficient feature extraction ability.
Bo Chen, Hongying Tang, Zebin Zhang, Guanjun Tong, Baoqing Li   +4 more
doaj   +1 more source

Transfer of Learning in the Convolutional Neural Networks on Classifying Geometric Shapes Based on Local or Global Invariants

Frontiers in Computational Neuroscience, 2021
The convolutional neural networks (CNNs) are a powerful tool of image classification that has been widely adopted in applications of automated scene segmentation and identification. However, the mechanisms underlying CNN image classification remain to be
Yufeng Zheng, Jun Huang, Tianwen Chen, Yang Ou, Wu Zhou   +4 more
doaj   +1 more source

REAL TIME EMBBEDED RGB-D SLAM USING CNNS FOR DEPTH ESTIMATION AND FEATURE EXTRACTION [PDF]

, 2023
"A robust and efficient Simultaneous Localization and Mapping (SLAM) system is essential for intelligent mobile robots to work in unknown environments.
Marcos Renato Rocha Hernández
core  

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Prevalence of wasting and its associated factors among children under 5 years of age in India: Findings from the comprehensive national nutrition survey

Indian Journal of Public Health
Background: The burden of wasting among under five children in India, has not reduced in the last decade. Objectives: We used child-level data from the latest nationally representative Comprehensive National Nutritional Survey (CNNS) to estimate the ...
Tarun Shankar Choudhary, Rukman Manapurath, Ranadip Chowdhury, Sunita Taneja, Abner Daniel, Robert Johnston, Arjan de Wagt, Nita Bhandari   +7 more
doaj   +1 more source

Demystifying CNNs for Images by Matched Filters

, 2022
The success of convolution neural networks (CNN) has been revolutionising the way we approach and use intelligent machines in the Big Data era. Despite success, CNNs have been consistently put under scrutiny owing to their \textit{black-box} nature, an ...
Li, Shengxi, Stankovic, Ljubisa, Mandic, Danilo, Zhao, Xinyi   +3 more
core  

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Bibliometric Analysis of the Application of Convolutional Neural Network in Computer Vision

IEEE Access, 2020
This article analyzes the research progress in field of Convolutional Neural Networks (CNNs) using the bibliometric method. Literature samples of CNNs are analyzed by a basic statistic and co-citation network.
Huie Chen, Zhenjie Deng
doaj   +1 more source

Coherentice: Invertible Concept-Based Explainability Framework for CNNs beyond Fidelity

In their natural form, convolutional neural networks (CNNs) lack interpretability despite their effectiveness in visual categorization. Concept activation vectors (CAVs) offer human-interpretable quantitative explainability, utilizing feature maps from ...
Gao, Y, Zhou, J, Akpudo, UE, Lewis, A
core   +1 more source