Results 61 to 70 of about 26,776 (176)

Tissue Engineered Human Elastic Cartilage From Primary Auricular Chondrocytes for Ear Reconstruction

Advanced Functional Materials, EarlyView.
Despite over three decades of research, no tissue‐engineered solution for auricular reconstruction in microtia patients has reached clinical translation. The key challenge lies in generating functional elastic cartilage ex vivo. Here, we integrate synergistic cell‐biomaterial strategies to engineer auricular grafts with mechanical and histological ...
Philipp Fisch, Sandra Kessler, Simone Ponta, Anna Puiggalí‐Jou, Guoliang Lyu, Killian Flégeau, Anastasiya Martyts, Florian Roth, David Fercher, Filippo M. Rijli, Daniel Simmen, Eva Novoa Olivares, Thomas Linder, Marcy Zenobi‐Wong   +13 more
wiley   +1 more source

Optimization Method for Classifier Output Repeatability Based on Siamese Networks [PDF]

Jisuanji gongcheng
In industrial surface Quality Control (QC) scenarios, deep classification neural networks are widely used to classify product images for qualified judgment or quality grading.
YU Yongtao, SUN Ao, LI Ang, ZHU Linlin
doaj   +1 more source

Matching Natural Language Sentences with Hierarchical Sentence Factorization

, 2018
Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks.
Han, Fred X., Lai, Kunfeng, Liu, Bang, Niu, Di, Xu, Yu, Zhang, Ting   +5 more
core   +1 more source

Smart Contract Vulnerability Detection Model Based on Siamese Network (SCVSN): A Case Study of Reentrancy Vulnerability

Energies, 2022
Blockchain technology is currently evolving rapidly, and smart contracts are the hallmark of the second generation of blockchains. Currently, smart contracts are gradually being used in power system networks to build a decentralized energy system ...
Ran Guo, Weijie Chen, Lejun Zhang, Guopeng Wang, Huiling Chen   +4 more
doaj   +1 more source

Siamese Capsule Networks

, 2018
Capsule Networks have shown encouraging results on \textit{defacto} benchmark computer vision datasets such as MNIST, CIFAR and smallNORB. Although, they are yet to be tested on tasks where (1) the entities detected inherently have more complex internal representations and (2) there are very few instances per class to learn from and (3) where point ...
openaire   +2 more sources

Semantic and context features integration for robust object tracking

IET Image Processing, 2022
Siamese network‐based object tracking learns features of a target object marked in the first frame and that of the object in subsequent frames simultaneously and then measures similarity between two features to recognize and locate the object.
Jinzhen Yao, Jianlin Zhang, Zhixing Wang, Linsong Shao   +3 more
doaj   +1 more source

Remote sensing scene classification based on rotation-invariant feature learning and joint decision making

EURASIP Journal on Image and Video Processing, 2019
With the popular use of high-resolution satellite images, remote sensing scene classification has always been a hot research topic in its related areas. However, limited to the issues of remote sensing datasets including the small scale of scene classes,
Yong Zhou, Xuning Liu, Jiaqi Zhao, Ding Ma, Rui Yao, Bing Liu, Yi Zheng   +6 more
doaj   +1 more source

Siamese Visual Tracking With Deep Features and Robust Feature Fusion

IEEE Access, 2020
Trackers based on fully-convolutional Siamese networks regard tracking as a process of learning a similarity function. By utilizing shallow networks and off-line training, Siamese trackers can achieve high tracking speed and perform well in some simple ...
Daqun Li, Xize Wang, Yi Yu
doaj   +1 more source

Bird Detection using Siamese Neural Network

International Journal of Innovative Technology and Exploring Engineering, 2020
The proposed system uses deep neural networks for identifying bird species. The model will be trained on bird images that are coming in the endangered species category. The application can also handle new data points, unlike existing systems that require model re-training for accommodating new data.
Rushil Gupta*, Shashank Pandey, D Vanusha   +2 more
openaire   +1 more source

Facial emotion recognition using deep Siamese neural networks: multi-classifier fusion for single-emotion and multi-emotion models across age groups

Journal of Big Data
This research examines facial expressions as social cues in online platforms, focusing on online learning and remote work. Our high-accuracy emotion recognition framework is designed for post-session evaluation, aiding teaching strategies and identifying
Tejas Rathod, Shruti Patil, Aniket K. Shahade, Prachi Kadam, Ambarish Kulkarni   +4 more
doaj   +1 more source