- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Computer-automated tuning procedures for semiconductor quantum dot arrays
摘要： As with any quantum computing platform, semiconductor quantum dot devices require sophisticated hardware and controls for operation. The increasing complexity of quantum dot devices necessitates the advancement of automated control software and image recognition techniques for rapidly evaluating charge stability diagrams. We use an image analysis toolbox developed in Python to automate the calibration of virtual gates, a process that previously involved a large amount of user intervention. Moreover, we show that straightforward feedback protocols can be used to simultaneously tune multiple tunnel couplings in a triple quantum dot in a computer automated fashion. Finally, we adopt the use of a “tunnel coupling lever arm” to model the interdot barrier gate response and discuss how it can be used to more rapidly tune interdot tunnel couplings to the gigahertz values that are compatible with exchange gates.
关键词： image recognition,tunnel couplings,automated control software,virtual gates,semiconductor quantum dot devices,charge stability diagrams,quantum computing
更新于2025-09-11 14:15:04
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A Combined Events Recognition Scheme Using Hybrid Features in Distributed Optical Fiber Vibration Sensing System
摘要： In this paper, a high efficiency multiple events recognition scheme based on a hybrid feature extraction algorithm and a combined classifier for distributed optical fiber vibration sensing (DOFVS) system has been proposed and demonstrated. The hybrid feature vectors are extracted by using zero crossing rate, sample entropy, wavelet packet energy entropy, kurtosis, and multiscale permutation entropy. A combined classifier of support vector machine and radial basis function neural network is proposed to improve the reliability of the recognition results. The recognition result is given only when both of the two classifiers output same event types. The experimental results demonstrated that the average identification rate of five typical patterns (no intrusion, waggling the fence, climbing the fence, kicking the fence, and cutting the fence) over 97% is achieved through the combined classifier. Moreover, the whole recognition processing speed of the combined scheme is also good of real time performance, which can be limited in 1.1 s. Therefore, this kind of events recognition scheme has a quite promising application prospects in DOFVS system.
关键词： hybrid feature vectors,signal analysis,Distributed vibration sensing,events recognition,optical fiber,combined classifier
更新于2025-09-11 14:15:04
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[IEEE 2018 4th International Conference on Frontiers of Signal Processing (ICFSP) - Poitiers, France (2018.9.24-2018.9.27)] 2018 4th International Conference on Frontiers of Signal Processing (ICFSP) - Real Time Finger Typing Recognition on iPhone’s RGB Camera
摘要： Recently, information processing capability has improved. Many softwares using cameras have increased, and the image processing can be performed in real time. The Original Character Input System proposed this real time composed of a character input system for the iPad application. Is a method of touching the tablet screen with five fingers and inputting characters with different combinations. The system proposed this real time picture taking of a finger typing on the camera of the smartphone then recognizes the typing fingertip in real time with the characters being inputted. As a result of the verification of the iPhone 8, the system can be processed with 30 FPS when the captured image with the size of 640 x 480 and the CPU usage rate of approximately 95%. In addition, the recognition rate for each finger typing is 100%.
关键词： real time,finger recognition,segmentation,iPhone
更新于2025-09-11 14:15:04
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[IEEE 2017 14th IEEE India Council International Conference (INDICON) - Roorkee (2017.12.15-2017.12.17)] 2017 14th IEEE India Council International Conference (INDICON) - Non-parametric Iris Localization Using Pupil's Uniform Intensities and Adaptive Masking
摘要： Iris localization is one of the vigorous components of any iris recognition system. It deals with the separation of annular iris from the acquired eye image. Accuracy of the iris segmentation module directly affects the overall system accuracy. In order to localize the pupillary boundary, this work utilizes local binary pattern (LBP) to exploit the uniform intensities present in the pupil region, to detect its boundaries. LBP aids in reducing the adverse effects of eyelashes in pupil localization. Moreover, an adaptive mask is also developed for localizing the limbus boundary. This mask provides a mean to combat with the varying sizes of iris due to variation in illumination. Outcomes of experiments performed with two benchmark iris databases (i.e. CASIA-IrisV1 and IITD iris database) support the efficacy of the proposed approach.
关键词： adaptive masks.,iris recognition,iris localization,local binary pattern (LBP)
更新于2025-09-11 14:15:04
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[IEEE 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT) - Lviv, Ukraine (2018.9.11-2018.9.14)] 2018 IEEE 13th International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT) - The Methods for Evaluating the Quality of Images with Different Types of Noise
摘要： In the context of evaluating the quality of image recognition systems, it's worth noting that noise is not the only type of interference. Performing such actions on the image as, for example, purposeful modification, rotation or zooming of the image will also have a negative effect on the image resolution. It has been established that one of the reasons for the complication of the decision-making process is the deterioration of the quality of the input information obtained on the basis of various images due to overlaying noise on them, which may have different origin and characteristics. Studying a certain class of noise in the context of considering it as a function allows you to focus on determining its parameters, the degree of influence of these parameters and the artificial noise generation. An overview of the noise of different types and their effects was performed for further evaluation of recognition systems. Noises that arise in this case, are subject to classification in order to study, formalize and further eliminate or minimize their harmful effects. Studying a certain class of noise in the context of considering it as a function allows you to focus on determining its parameters, the degree of influence of these parameters and the artificial noise generation.
关键词： recognition systems quality evaluation,speckle noise,Perlin noise,Gaussian noise,Poisson noise,noise overlaying methods,photographic film grains noise
更新于2025-09-11 14:15:04
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[IEEE 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS) - Edinburgh, United Kingdom (2018.8.6-2018.8.9)] 2018 NASA/ESA Conference on Adaptive Hardware and Systems (AHS) - Towards the design of smart video-surveillance system
摘要： Security and monitoring systems are increasingly demanding in terms of quality, reliability and ?exibility especially those dedicated to video surveillance. The aim of this study is to identify some limiting factors in the existing video-surveillance systems and to propose a set of best practices for developing a smart platform for a security monitoring system incorporating advanced techniques for video processing and analysis. In this work, we focus on the effect of the video quality on the biometric part of the video-surveillance systems for public security. In such systems, face detection and recognition from video sequences acquired from surveillance cameras, are challenging tasks, due to presence of strong illumination variations, noise, and changes in facial expressions. In this paper, we mainly focus on the illumination issue occurred in video surveillance. The low light video data is processed using a perceptual based approach, namely multi-scale Retinex method, to improve the video quality, followed by face detection. The experimental results demonstrate signi?cant performance improvement in face detection and recognition, by improving the illumination of video sequences over the unprocessed video data.
关键词： Retinex,face recognition,face detection,video surveillance,enhancement
更新于2025-09-11 14:15:04
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Ensemble of Multi-View Learning Classifiers for Cross-Domain Iris Presentation Attack Detection
摘要： The adoption of large-scale iris recognition systems around the world has brought the importance of detecting presentation attack images (textured contact lenses and printouts). This work presents a new approach in iris Presentation Attack Detection (PAD), by exploring combinations of Convolutional Neural Networks (CNNs) and transformed input spaces through binarized statistical image features (BSIF). Our method combines lightweight CNNs to classify multiple BSIF views of the input image. Following explorations on complementary input spaces leading to more discriminative features to detect presentation attacks, we also propose an algorithm to select the best (and most discriminative) predictors for the task at hand. An ensemble of predictors makes use of their expected individual performances to aggregate their results into a final prediction. Results show that this technique improves on the current state of the art in iris PAD, outperforming the winner of LivDet-Iris 2017 competition both for intra- and cross-dataset scenarios, and illustrating the very difficult nature of the cross-dataset scenario.
关键词： Convolutional Neural Networks (CNNs),Ensemble Learning,Binarized Statistical Image Features (BSIF),Presentation Attack Detection (PAD),Iris recognition
更新于2025-09-11 14:15:04
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Target recognition system of dynamic scene based on artificial intelligence vision
摘要： Using the current recognition system to recognize dynamic scene cannot effectively speed up the target recognition. When target recognition increases, the accuracy of target recognition is relatively low. In order to solve this problem, a target recognition system of dynamic scene based on DSP was designed. Combined with the idea of DSP system design, the design process and composition of target recognition system was expounded. The recognition algorithm based on spatial-temporal condition information was used to realize the designed recognition system. By introducing the visual attention mechanism, the spatial-temporal domain model based on visual significance was built. The pixel neighborhood weighted condition information was used as classification features to enhance the linear separability for target and background and improve the recognition accuracy of dynamic scene moving target. Finally, combined with image block modeling strategy, the efficient and real-time recognition of moving target in dynamic scene was realized. Experimental results show that the proposed target recognition system can effectively improve the accuracy of target recognition.
关键词： Artificial intelligence vision,recognition system,dynamic scene,target recognition
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE International Conference on Electro/Information Technology (EIT) - Rochester, MI (2018.5.3-2018.5.5)] 2018 IEEE International Conference on Electro/Information Technology (EIT) - A Survey of Traffic Sign Recognition Systems Based on Convolutional Neural Networks
摘要： In this paper, we briefly discuss the applications of Convolutional Neural Networks (CNNs) model to traffic sign recognition (TSR) systems. Traditionally, the TSRs have used different techniques to detect and classify visual data. The CNNs have been used separately to extract features and train the classifier as well as simultaneously for detection and classification tasks. One model that has been successful is the Fast Branch CNN model, which imitates biological mechanisms to become more efficient. While it is not the most accurate of the ones presented in this paper, the efficiency it exhibits under time-sensitive conditions is worth exploring because of the potential applications of such technology. The Fast Branch CNN model challenged the assumptions of past models, and this technology can only advance further if new models attempt to do the same.
关键词： CNN (Convolutional Neural Network),TSR (Traffic Sign Recognition),Classification,Detection
更新于2025-09-10 09:29:36
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[IEEE 2018 IEEE International Conference on Robotics and Automation (ICRA) - Brisbane, QLD (2018.5.21-2018.5.25)] 2018 IEEE International Conference on Robotics and Automation (ICRA) - Delight: An Efficient Descriptor for Global Localisation Using LiDAR Intensities
摘要： Place recognition is a key element of mobile robotics. It can assist with the “wake-up” and “kidnapped robot” problems, where the robot position needs to be estimated without prior information. Among the different sensors that can be used for the task (e.g., camera, GPS, LiDAR), LiDAR has the advantage of operating in the dark and in GPS-denied areas. We propose a new method that uses solely the LiDAR data and that can be performed without robot motion. In contrast to other methods, our system leverages intensity information (as opposed to only range information) which is encoded into a novel descriptor of LiDAR intensities as a group of histograms, named DELIGHT. The descriptor encodes the distributed histograms of intensity of the surroundings which are compared using chi-squared tests. Our pipeline is a two-stage solution consisting of an intensity-based prior estimation and a geometry-based verification. For a map of 220k square meters, the method achieves localisation in around 3s with a success rate of 97%, illustrating the applicability of the method in real environments.
关键词： global localisation,Place recognition,DELIGHT descriptor,LiDAR,intensity information
更新于2025-09-10 09:29:36