Results 61 to 70 of about 5,528,069 (258)

Algorithm of integrated dimensionality reduction convolutional neural network (IDRCNN).

, 2023
Algorithm of integrated dimensionality reduction convolutional neural network (IDRCNN).
HuanQing Xu (15419057), Li Jin (40265), Xian Shao (9339225), Shiji Hui (15419060)   +3 more
core   +1 more source

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

Gesture recognition based on convolutional neural network

, 2022
This topic uses convolutional neural network deep learning algorithm technology to design a gesture ...
Cheng Peng
core   +1 more source

FocusedDropout for Convolutional Neural Network

Applied Sciences, 2022
In a convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially.
Minghui Liu, Tianshu Xie, Xuan Cheng, Jiali Deng, Meiyi Yang, Xiaomin Wang, Ming Liu   +6 more
doaj   +1 more source

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

A Frequency-Domain Convolutional Neural Network Architecture Based on the Frequency-Domain Randomized Offset Rectified Linear Unit and Frequency-Domain Chunk Max Pooling Method

IEEE Access, 2020
It is of great importance to construct a convolutional neural network architecture in the frequency domain to explore the theory of deep learning in the frequency domain.
Jinhua Lin, Lin Ma, Jingxia Cui
doaj   +1 more source

ST-CNN: Spatial-Temporal Convolutional Neural Network for crowd counting in videos

, 2019
The task of crowd counting and density maps estimating from videos is challenging due to severe occlusions, scene perspective distortions and diverse crowd distributions.
Gao, Y, Han, J, Zhang, B, Miao, Y
core   +1 more source

Augmented Reality based 3D Human Hands Tracking from Monocular True Images Using Convolutional Neural Network [PDF]

, 2023
Precise modeling of hand tracking from monocular moving camera calibration parameters using semantic cues is an active area of research concern for the researchers due to lack of accuracy and computational overheads.
Saif, A F M Saifuddin, Mahayuddin, Zainal Rasyid   +1 more
core   +1 more source

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

A classification method of underwater target radiated noise signals based on enhanced images and convolutional neural networks

Frontiers in Physics
As the economy and society continue to develop, the range of underwater vehicles is expanding and technology is constantly being upgraded. Consequently, it is becoming increasingly difficult to classify and identify them, and the traditional ...
Yuan Muye, Lei Zhufeng, Dang Yinuo, Shi Zanrong   +3 more
doaj   +1 more source