Direct laser-patterned MXene–perovskite image sensor arrays for visible-near infrared photodetection

2020 ◽  
Vol 7 (7) ◽  
pp. 1901-1911 ◽  
Author(s):  
Aobo Ren ◽  
Jihua Zou ◽  
Huagui Lai ◽  
Yixuan Huang ◽  
Liming Yuan ◽  
...  
Keyword(s):  
Near Infrared ◽  
Performance Metrics ◽  
State Of The Art ◽  
Sensor Arrays ◽  
Image Sensor ◽  
Top Down ◽  
Solution Processed ◽  
Direct Laser ◽  
Infrared Photodetection ◽  
Art Performance

Solution-processed MXene–perovskite image sensor arrays are realized by a top-down method, which combine desirable manufacturing advantages and state-of-the-art performance metrics.

HgCdTe photodiodes with state-of-the-art performance in the near- infrared spectral region

2001 ◽  
Author(s):  
Honnavalli R. Vydyanath ◽  
Stephen P. Tobin ◽  
Peter W. Norton ◽  
P. Odette ◽  
Vaidya Nathan
Keyword(s):  
Spectral Region ◽  
Near Infrared ◽  
State Of The Art ◽  
Infrared Spectral Region ◽  
Infrared Spectral ◽  
Art Performance ◽  
Hgcdte Photodiodes

scholarly journals Automatically Designing State-of-the-Art Multi- and Many-Objective Evolutionary Algorithms

2020 ◽  
Vol 28 (2) ◽  
pp. 195-226 ◽  
Author(s):  
Leonardo C. T. Bezerra ◽  
Manuel López-Ibáñez ◽  
Thomas Stützle
Keyword(s):  
Evolutionary Algorithms ◽  
Performance Metrics ◽  
State Of The Art ◽  
Continuous Optimization ◽  
Parameter Tuning ◽  
High Performing ◽  
Performance Metric ◽  
Wide Range ◽  
Algorithmic Framework ◽  
Art Performance

A recent comparison of well-established multiobjective evolutionary algorithms (MOEAs) has helped better identify the current state-of-the-art by considering (i) parameter tuning through automatic configuration, (ii) a wide range of different setups, and (iii) various performance metrics. Here, we automatically devise MOEAs with verified state-of-the-art performance for multi- and many-objective continuous optimization. Our work is based on two main considerations. The first is that high-performing algorithms can be obtained from a configurable algorithmic framework in an automated way. The second is that multiple performance metrics may be required to guide this automatic design process. In the first part of this work, we extend our previously proposed algorithmic framework, increasing the number of MOEAs, underlying evolutionary algorithms, and search paradigms that it comprises. These components can be combined following a general MOEA template, and an automatic configuration method is used to instantiate high-performing MOEA designs that optimize a given performance metric and present state-of-the-art performance. In the second part, we propose a multiobjective formulation for the automatic MOEA design, which proves critical for the context of many-objective optimization due to the disagreement of established performance metrics. Our proposed formulation leads to an automatically designed MOEA that presents state-of-the-art performance according to a set of metrics, rather than a single one.

Solution-Processed Gold Nanorods Integrated with Graphene for Near-Infrared Photodetection via Hot Carrier Injection

2015 ◽  
Vol 7 (43) ◽  
pp. 24136-24141 ◽  
Author(s):  
Zhouhui Xia ◽  
Pengfei Li ◽  
Yusheng Wang ◽  
Tao Song ◽  
Qiao Zhang ◽  
...  
Keyword(s):  
Gold Nanorods ◽  
Near Infrared ◽  
Carrier Injection ◽  
Solution Processed ◽  
Hot Carrier ◽  
Hot Carrier Injection ◽  
Infrared Photodetection

High-mobility nanometer-thick crystalline In–Sm–O thin-film transistors via aqueous solution processing

2020 ◽  
Vol 8 (1) ◽  
pp. 310-318 ◽  
Author(s):  
Yanwei Li ◽  
Deliang Zhu ◽  
Wangying Xu ◽  
Shun Han ◽  
Ming Fang ◽  
...  
Keyword(s):  
Thin Film ◽  
Aqueous Solution ◽  
Thin Film Transistors ◽  
State Of The Art ◽  
High Mobility ◽  
Solution Processing ◽  
Solution Processed ◽  
Art Performance

We demonstrated aqueous solution-processed In–Sm–O TFTs with state-of-the-art performance.

scholarly journals Bottom-up and Layerwise Domain Adaptation for Pedestrian Detection in Thermal Images

2021 ◽  
Vol 17 (1) ◽  
pp. 1-19
Author(s):  
My Kieu ◽  
Andrew D. Bagdanov ◽  
Marco Bertini
Keyword(s):  
Domain Adaptation ◽  
State Of The Art ◽  
Pedestrian Detection ◽  
Challenging Problem ◽  
Top Down ◽  
Bottom Up ◽  
Security Applications ◽  
Lighting Conditions ◽  
Initial Layers ◽  
Single Modality

Pedestrian detection is a canonical problem for safety and security applications, and it remains a challenging problem due to the highly variable lighting conditions in which pedestrians must be detected. This article investigates several domain adaptation approaches to adapt RGB-trained detectors to the thermal domain. Building on our earlier work on domain adaptation for privacy-preserving pedestrian detection, we conducted an extensive experimental evaluation comparing top-down and bottom-up domain adaptation and also propose two new bottom-up domain adaptation strategies. For top-down domain adaptation, we leverage a detector pre-trained on RGB imagery and efficiently adapt it to perform pedestrian detection in the thermal domain. Our bottom-up domain adaptation approaches include two steps: first, training an adapter segment corresponding to initial layers of the RGB-trained detector adapts to the new input distribution; then, we reconnect the adapter segment to the original RGB-trained detector for final adaptation with a top-down loss. To the best of our knowledge, our bottom-up domain adaptation approaches outperform the best-performing single-modality pedestrian detection results on KAIST and outperform the state of the art on FLIR.

Electrostatically Tunable Near‐Infrared Plasmonic Resonances in Solution‐Processed Atomically Thin NbSe 2

2021 ◽  
pp. 2101950
Author(s):  
Meng Zhao ◽  
Jing Li ◽  
Matej Sebek ◽  
Le Yang ◽  
Yan Jun Liu ◽  
...  
Keyword(s):  
Near Infrared ◽  
Solution Processed

scholarly journals PyConvU-Net: a lightweight and multiscale network for biomedical image segmentation

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Changyong Li ◽  
Yongxian Fan ◽  
Xiaodong Cai
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
State Of The Art ◽  
Experimental Results ◽  
Actual Situation ◽  
Controlled Experiments ◽  
Biomedical Image ◽  
Segmentation Methods ◽  
Art Performance

Abstract Background With the development of deep learning (DL), more and more methods based on deep learning are proposed and achieve state-of-the-art performance in biomedical image segmentation. However, these methods are usually complex and require the support of powerful computing resources. According to the actual situation, it is impractical that we use huge computing resources in clinical situations. Thus, it is significant to develop accurate DL based biomedical image segmentation methods which depend on resources-constraint computing. Results A lightweight and multiscale network called PyConvU-Net is proposed to potentially work with low-resources computing. Through strictly controlled experiments, PyConvU-Net predictions have a good performance on three biomedical image segmentation tasks with the fewest parameters. Conclusions Our experimental results preliminarily demonstrate the potential of proposed PyConvU-Net in biomedical image segmentation with resources-constraint computing.

scholarly journals Regulating disordered plasmonic nanoparticles into polarization sensitive metasurfaces

Nanophotonics ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shulei Li ◽  
Mingcheng Panmai ◽  
Shaolong Tie ◽  
Yi Xu ◽  
Jin Xiang ◽  
...  
Keyword(s):  
Femtosecond Laser ◽  
Spatial Resolution ◽  
Metallic Nanoparticles ◽  
Near Infrared ◽  
Optical Memory ◽  
Laser Pulses ◽  
Femtosecond Laser Pulses ◽  
Optical Diffraction ◽  
Plasmonic Nanoparticles ◽  
Direct Laser

Abstract Metasurfaces composed of regularly arranged and deliberately oriented metallic nanoparticles can be employed to manipulate the amplitude, phase and polarization of an incident electromagnetic wave. The metasurfaces operating in the visible to near infrared spectral range rely on the modern fabrication technologies which offer a spatial resolution beyond the optical diffraction limit. Although direct laser writing is an alternative to the fabrication of nanostructures, the achievement of regular nanostructures with deep-subwavelength periods by using this method remains a big challenge. Here, we proposed and demonstrated a novel strategy for regulating disordered plasmonic nanoparticles into nanogratings with deep-subwavelength periods and reshaped nanoparticles by using femtosecond laser pulses. The orientations of the nanogratings depend strongly on the polarization of the femtosecond laser light. Such nanogratings exhibit reflection and polarization control over the reflected light, enabling the realization of polarization sensitive optical memory and color display with high spatial resolution and good chromacity.

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