Results 51 to 60 of about 11,957 (239)

Automatic Target Recognition (ATR) System using Recurrent Neural Network (RNN) for Pulse Radar

International Journal of Computer Applications, 2012
The most fundamental problem in radar is the detection of an object or a physical phenomenon. This requires proper discrimination between signal and noise content at the receiver even after the echo containing target information is surrounded by clutter.
Kandarpa Kumar Sarma, Kaustubh Bhattacharyya   +1 more
openaire   +1 more source

"Sticky Hands": learning and generalization for cooperative physical interactions with a humanoid robot [PDF]

, 2005
"Sticky Hands" is a physical game for two people involving gentle contact with the hands. The aim is to develop relaxed and elegant motion together, achieve physical sensitivity-improving reactions, and experience an interaction at an intimate yet ...
Hale, J.G., Pollick, F.E.
core   +1 more source

Direct Synthesis of High‐Valence Protein@UiO‐66 Composites: Linking Crystallization Pathways to Protein Encapsulation

Advanced Materials, EarlyView.
This work reports a direct, biocompatible method to synthesize UiO‐66, enabling one‐step encapsulation of proteins without compromising crystallinity or activity. Using advanced in situ and ex situ techniques, the study reveals that proteins integrate concurrently with MOF growth, forming crystalline protein@UiO‐66 nanoparticles, and provide insight ...
Jesús Cases Díaz, Jana Glatz, Elisa Merced Olivas, Ramon Pons, Joseph P. Patterson, Mónica Giménez‐Marqués   +5 more
wiley   +1 more source

Accurate Underwater ATR in Forward-Looking Sonar Imagery Using Deep Convolutional Neural Networks

IEEE Access, 2019
Underwater automatic target recognition (ATR) is a challenging task for marine robots due to the complex environment. The existing recognition methods basically use hand-crafted features and classifiers to recognize targets, which are difficult to ...
Leilei Jin, Hong Liang, Changsheng Yang
doaj   +1 more source

Semi-Supervised SAR ATR Framework with Transductive Auxiliary Segmentation

Remote Sensing, 2022
Convolutional neural networks (CNNs) have achieved high performance in synthetic aperture radar (SAR) automatic target recognition (ATR). However, the performance of CNNs depends heavily on a large amount of training data.
Chenwei Wang, Xiaoyu Liu, Yulin Huang, Siyi Luo, Jifang Pei, Jianyu Yang, Deqing Mao   +6 more
doaj   +1 more source

Sparse representation-based synthetic aperture radar imaging [PDF]

, 2011
There is increasing interest in using synthetic aperture radar (SAR) images in automated target recognition and decision-making tasks. The success of such tasks depends on how well the reconstructed SAR images exhibit certain features of the underlying ...
Cetin, Mujdat, Masnadi-Shirazi, Mohammad Ali, Samadi, Sadegh, Çetin, Müjdat   +3 more
core   +1 more source

End‐to‐End Sensing Systems for Breast Cancer: From Wearables for Early Detection to Lab‐Based Diagnosis Chips

Advanced Materials Technologies, EarlyView.
This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane, Lyn I. Jones, Richard M. Martin, Helen Winter, Faezeh Arab Hassani   +4 more
wiley   +1 more source

SAR Target Recognition via Meta-Learning and Amortized Variational Inference

Sensors, 2020
The challenge of small data has emerged in synthetic aperture radar automatic target recognition (SAR-ATR) problems. Most SAR-ATR methods are data-driven and require a lot of training data that are expensive to collect.
Ke Wang, Gong Zhang
doaj   +1 more source

Feature Learning for SAR Target Recognition with Unknown Classes by Using CVAE-GAN

Remote Sensing, 2021
Even though deep learning (DL) has achieved excellent results on some public data sets for synthetic aperture radar (SAR) automatic target recognition(ATR), several problems exist at present.
Xiaowei Hu, Weike Feng, Yiduo Guo, Qiang Wang   +3 more
doaj   +1 more source

3D Printing of Stretchable, Compressible and Conductive Porous Polyurethane for Soft Robotics

Advanced Materials Technologies, EarlyView.
A 3D‐printable porous dopamine‐polyurethane acrylate elastomer results in conductive, stretchable, and compressible structures that can be metallized in situ through catechol‐mediated silver reduction. The resulting material function as both compliant soft robot with a and strain sensors without complex assemblies, enabling fully 3D‐printed soft ...
Ouriel Bliah, Konstantin Sakharov, Pooi See Lee, Shlomo Magdassi   +3 more
wiley   +1 more source