Mine detection technologies essential to survivability

1995 ◽  
Author(s):  
Robert L. Barnard
Keyword(s):  
Mine Detection ◽  
Detection Technologies

An AHP-Based Evaluating Model to Evaluate Intelligent Vehicle Detection Technologies in Street Parking Scenario

CICTP 2018 ◽  
2018 ◽  
Author(s):  
Xuejin Wan ◽  
Shangfo Huang ◽  
Bowen Du ◽  
Rui Sun ◽  
Jiong Wang ◽  
...  
Keyword(s):  
Vehicle Detection ◽  
Intelligent Vehicle ◽  
Detection Technologies

Magnetic Background Survey for UXO and Mine Detection

1996 ◽  
Author(s):  
TRUSTEES OF COLUMBIA UNIV NEW YORK
Keyword(s):  
Mine Detection

scholarly journals The Effect of Informing Participants of the Response Bias of an Automated Target Recognition System on Trust and Reliance Behavior

2021 ◽  
pp. 001872082110217
Author(s):  
Shala Knocton ◽  
Aren Hunter ◽  
Warren Connors ◽  
Lori Dithurbide ◽  
Heather F. Neyedli
Keyword(s):  
Response Bias ◽  
Target Recognition ◽  
Rate Sensitivity ◽  
High Sensitivity ◽  
Recognition System ◽  
Decision Criterion ◽  
Detection Task ◽  
Mine Detection ◽  
Rate Condition ◽  
Consistent Response

Objective To determine how changing and informing a user of the false alarm (FA) rate of an automated target recognition (ATR) system affects the user’s trust in and reliance on the system and their performance during an underwater mine detection task. Background ATR systems are designed to operate using a high sensitivity and a liberal decision criterion to reduce the risk of the ATR system missing a target. A high number of FAs in general may lead to a decrease in operator trust and reliance. Methods Participants viewed sonar images and were asked to identify mines in the images. They performed the task without ATR and with ATR at a lower and higher FA rate. The participants were split into two groups—one informed and one uninformed of the changed FA rate. Trust and/or confidence in detecting mines was measured after each block. Results When not informed of the FA rate, the FA rate had a significant effect on the participants’ response bias. Participants had greater trust in the system and a more consistent response bias when informed of the FA rate. Sensitivity and confidence were not influenced by disclosure of the FA rate but were significantly worse for the high FA rate condition compared with performance without the ATR. Conclusion and application Informing a user of the FA rate of automation may positively influence the level of trust in and reliance on the aid.

scholarly journals Recent Advancements in Enzyme-Based Lateral Flow Immunoassays

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3358
Author(s):  
Donato Calabria ◽  
Maria Maddalena Calabretta ◽  
Martina Zangheri ◽  
Elisa Marchegiani ◽  
Ilaria Trozzi ◽  
...  
Keyword(s):  
Lateral Flow ◽  
Qualitative Information ◽  
Eye Color ◽  
Commercial Success ◽  
Color Changes ◽  
Naked Eye ◽  
Future Developments ◽  
Highly Sensitive ◽  
Critical Overview ◽  
Detection Technologies

Paper-based lateral-flow immunoassays (LFIAs) have achieved considerable commercial success and their impact in diagnostics is continuously growing. LFIA results are often obtained by visualizing by the naked eye color changes in given areas, providing a qualitative information about the presence/absence of the target analyte in the sample. However, this platform has the potential to provide ultrasensitive quantitative analysis for several applications. Indeed, LFIA is based on well-established immunological techniques, which have known in the last year great advances due to the combination of highly sensitive tracers, innovative signal amplification strategies and last-generation instrumental detectors. All these available progresses can be applied also to the LFIA platform by adapting them to a portable and miniaturized format. This possibility opens countless strategies for definitively turning the LFIA technique into an ultrasensitive quantitative method. Among the different proposals for achieving this goal, the use of enzyme-based immunoassay is very well known and widespread for routine analysis and it can represent a valid approach for improving LFIA performances. Several examples have been recently reported in literature exploiting enzymes properties and features for obtaining significative advances in this field. In this review, we aim to provide a critical overview of the recent progresses in highly sensitive LFIA detection technologies, involving the exploitation of enzyme-based amplification strategies. The features and applications of the technologies, along with future developments and challenges, are also discussed.

scholarly journals Chinese Character Image Completion Using a Generative Latent Variable Model

2021 ◽  
Vol 11 (2) ◽  
pp. 624
Author(s):  
In-su Jo ◽  
Dong-bin Choi ◽  
Young B. Park
Keyword(s):  
Latent Variable ◽  
Chinese Character ◽  
Image Inpainting ◽  
Latent Variable Model ◽  
Chinese Characters ◽  
Image Completion ◽  
Variable Model ◽  
Variational Autoencoder ◽  
Convolution Model ◽  
Detection Technologies

Chinese characters in ancient books have many corrupted characters, and there are cases in which objects are mixed in the process of extracting the characters into images. To use this incomplete image as accurate data, we use image completion technology, which removes unnecessary objects and restores corrupted images. In this paper, we propose a variational autoencoder with classification (VAE-C) model. This model is characterized by using classification areas and a class activation map (CAM). Through the classification area, the data distribution is disentangled, and then the node to be adjusted is tracked using CAM. Through the latent variable, with which the determined node value is reduced, an image from which unnecessary objects have been removed is created. The VAE-C model can be utilized not only to eliminate unnecessary objects but also to restore corrupted images. By comparing the performance of removing unnecessary objects with mask regions with convolutional neural networks (Mask R-CNN), one of the prevalent object detection technologies, and also comparing the image restoration performance with the partial convolution model (PConv) and the gated convolution model (GConv), which are image inpainting technologies, our model is proven to perform excellently in terms of removing objects and restoring corrupted areas.

scholarly journals Recent advances in radiation detection technologies enabled by metal-halide perovskites

2021 ◽  
Author(s):  
Tiebin Yang ◽  
Feng Li ◽  
Rongkun Zheng
Keyword(s):  
Gamma Rays ◽  
Performance Optimization ◽  
Radiation Detection ◽  
High Energy ◽  
Device Performance ◽  
High Energy Radiation ◽  
Energy Radiation ◽  
Halide Perovskites ◽  
Alpha Beta ◽  
Detection Technologies

Perovskite halides hold great potential for high-energy radiation detection. Recent advancements in detecting alpha-, beta-, X-, and gamma-rays by perovskite halides are reviewed and an outlook on the device performance optimization is provided.

Specific antigen‐based and emerging detection technologies of mycotoxins

2019 ◽  
Vol 99 (11) ◽  
pp. 4869-4877 ◽  
Author(s):  
Hamid Ur Rahman ◽  
Xiaofeng Yue ◽  
Qiuyu Yu ◽  
Huali Xie ◽  
Wen Zhang ◽  
...  
Keyword(s):  
Specific Antigen ◽  
Detection Technologies

scholarly journals Land Mine Detection Using Rocker Bogie System

2021 ◽  
Vol 1057 ◽  
pp. 012087
Author(s):  
Mahesh Kusuma ◽  
K Arun Kumar ◽  
G Vijay Goud ◽  
A Harika Reddy
Keyword(s):  
Mine Detection ◽  
Land Mine ◽  
Land Mine Detection
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