Results 41 to 50 of about 86,091 (310)

Supplementary Material (Paper CNNs in Education)

, 2022
Supplementary Material (Paper CNNs in Education)
Thiago Damasceno Cordeiro, Leonardo Brandão Marques, Alan Pedro da Silva, Álvaro Sobrinho, Francisco Leonardo Aureliano Ferreira, Rafael Ferreira Melo, Diego Dermeval, Ig Ibert Bittencourt, Seiji Isotani, Lenardo Chaves e Silva   +9 more
core   +1 more source

Prediction of Surface Topography Parameters in Direct Laser Interference Patterning of Stainless Steel Using Infrared Monitoring and Convolutional Neural Networks

Advanced Engineering Materials, EarlyView.
This study presents an infrared monitoring approach for direct laser interference patterning (DLIP) combined with a convolutional neural network (CNN). Thermal emission data captured during structuring are used to predict surface topography parameters.
Lukas Olawsky, Marcelo Sallese, Leander Kläber, Clemens Kuhn, Keming Du, Andrés Fabián Lasagni   +5 more
wiley   +1 more source

Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

Remote Sensing, 2017
Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to
Jie Wang, Chang Luo, Hanqiao Huang, Huizhen Zhao, Shiqiang Wang   +4 more
doaj   +1 more source

Ensemble of CNNs for Steganalysis

, 2016
There has been growing interest in using convolutional neural networks (CNNs) in the fields of image forensics and steganalysis, and some promising results have been reported recently. These works mainly focus on the architectural design of CNNs, usually,
Xu, Guanshuo, Wu, Han Zhou, Guanshuo Xu, Yun Q.. Shi, Shi, Yun Q., Han-Zhou Wu   +5 more
core   +1 more source

Enhancing CNNs Performance on Object Recognition Tasks with Gabor Initialization

, 2023
The use of Gabor filters in image processing has been well-established, and these filters are recognized for their exceptional feature extraction capabilities. These filters are usually applied through convolution.
Pablo Rivas, Mehang Rai
core   +1 more source

Texoskeletons: Developing the Fundamental Technologies for Creating Intelligent Soft Robotic Clothing With Integrated 1D Sensors and Actuators

Advanced Functional Materials, EarlyView.
ABSTRACT Traditional wearable exoskeletons rely on rigid structures, which limit comfort, flexibility, and everyday usability. This work introduces the fundamental technologies to create the first soft, lightweight, intelligent textile‐based exoskeletons (Texoskeletons) built using 1D sensors and actuators.
Amy Lukomiak, Rameesh Bulathsinghala, Jack Varga, Shuxin Meng, Kalana Marasinghe, Imaad Refai, Biyon Fernando, Amitkumar Patel, Chamika M. Halloluwa‐Arachchige, Carlos Oliveira, Arash M. Shahidi, Zahra Rahemtulla, Alexander Turner, Ziyun Ding, Bernard X. W. Liew, Andy Kerr, Ezio Preatoni, Theo Hughes‐Riley, Ishara Dharmasena, Pasindu Lugoda   +19 more
wiley   +1 more source

Focused Quantization for Sparse CNNs

, 2020
Deep convolutional neural networks (CNNs) are powerful tools for a wide range of vision tasks, but the enormous amount of memory and compute resources required by CNNs pose a challenge in deploying them on constrained devices.

core   +1 more source

Transparent and Robust LiCl–Organohydrogel Triboelectric Nanogenerator With Deep Learning Assisted Sensing

Advanced Functional Materials, EarlyView.
Develop a LiCl–PEI–PAM hydrogel with 3000% stretchability and excellent optical transparency. Through comparative studies of various salts, confirm that LiCl is the most suitable salt for high TENG output. Achieve excellent freeze‐resistant, dry‐resistant, and rapid self‐healing (10 s) properties even in extreme environments. Balance ionic conductivity,
Hai Anh Thi Le, Thien Trung Luu, Duc‐Manh Dinh, Kyehan Rhee, Kyungwho Choi, Dukhyun Choi, Yong Tae Park   +6 more
wiley   +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

OA-CNNs: Omni-Adaptive Sparse CNNs for 3D Semantic Segmentation

The booming of 3D recognition in the 2020s began with the introduction of point cloud transformers. They quickly overwhelmed sparse CNNs and became state-of-the-art models, especially in 3D semantic segmentation.
Wu, Xiaoyang, Peng, Bohao, Tian, Zhuotao, Jiang, Li, Chen, Yukang, Zhao, Hengshuang, Jia, Jiaya   +6 more
core   +2 more sources