- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Artificial optic-neural synapse for colored and color-mixed pattern recognition
摘要： The priority of synaptic device researches has been given to prove the device potential for the emulation of synaptic dynamics and not to functionalize further synaptic devices for more complex learning. Here, we demonstrate an optic-neural synaptic device by implementing synaptic and optical-sensing functions together on h-BN/WSe2 heterostructure. This device mimics the colored and color-mixed pattern recognition capabilities of the human vision system when arranged in an optic-neural network. Our synaptic device demonstrates a close to linear weight update trajectory while providing a large number of stable conduction states with less than 1% variation per state. The device operates with low voltage spikes of 0.3 V and consumes only 66 fJ per spike. This consequently facilitates the demonstration of accurate and energy efficient colored and color-mixed pattern recognition. The work will be an important step toward neural networks that comprise neural sensing and training functions for more complex pattern recognition.
关键词： optic-neural synaptic device,human vision system,pattern recognition,energy efficiency,h-BN/WSe2 heterostructure
更新于2025-09-23 15:21:21
-
[Communications in Computer and Information Science] Advances in Computing and Data Sciences Volume 905 (Second International Conference, ICACDS 2018, Dehradun, India, April 20-21, 2018, Revised Selected Papers, Part I) || Optical Character Recognition (OCR) of Marathi Printed Documents Using Statistical Approach
摘要： Optical Character Recognition (OCR) of local languages is an important research area as the techniques developed for one language cannot apply directly to other languages. The paper presents the development of a new statistical method based on template matching and modified template matching used for recognition of a local language of the State of Maharashtra Marathi. It is noted that proposed method not only gives good recognition rate but also have offered good CPU and memory efficiency. Along with system accuracy, average CPU consumption and memory utilization is also analyses and found the acceptable minimum. The proposed algorithm for Marathi OCR is optimized for speed compared with the existing algorithm and hence permits porting on handheld devices with low processing power like Mobile phones. The algorithm is robust in terms of characters size and style of writing.
关键词： OCR,Devanagari Marathi character recognition,Statistical feature extraction
更新于2025-09-23 15:21:21
-
Parking Space and Obstacle Detection Based on a Vision Sensor and Checkerboard Grid Laser
摘要： The accuracy of automated parking technology that uses ultrasonic radar or camera vision for obstacles and parking space identification can easily be affected by the surrounding environment especially when the color of the obstacles is similar to the ground. Additionally, this type of system cannot recognize the size of the obstacles detected. This paper proposes a method to identify parking spaces and obstacles based on visual sensor and laser device recognition methods by installing a laser transmitter on the car. The laser transmitter produces a checkerboard-shaped laser grid (mesh), which varies with the condition encountered on the ground, which is then captured by the camera and taken as the region of interest for the necessary image processing. The experimental results show that this method can effectively identify obstacles as well as their size and parking spaces even when the obstacles and the background have a similar color compared to when only using sensors or cameras alone.
关键词： machine vision,parking space recognition,checkerboard-shaped laser grid,obstacle recognition
更新于2025-09-23 15:21:01
-
[IEEE 2019 IEEE SENSORS - Montreal, QC, Canada (2019.10.27-2019.10.30)] 2019 IEEE SENSORS - Optical sensor based on pseudo-random diffractive optical elements for reliable gesture reconstruction
摘要： Biometric template aging is defined as an increase in recognition error rate with increased time since enrollment. It is believed that template aging does not occur for iris recognition. Several research groups, however, have recently reported experimental results showing that iris template aging does occur. This template aging effect manifests as a shift in the authentic distribution, resulting in an increased false non-match rate. Analyzing results from a three-year time-lapse data set, we find ～ 150% increase in the false non-match rate at a decision threshold representing a one in two million false match rate. We summarize several known elements of eye aging that could contribute to template aging, including age-related change in pupil dilation. Finally, we discuss various steps that can control the template aging effect in typical identity verification applications.
关键词： false non-match rate,iris recognition,Biometrics,error probability,template aging
更新于2025-09-23 15:21:01
-
[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - A Multi-Copy Approach to Quantum Entanglement Characterization
摘要： Automatic speech recognition (ASR) systems are used daily by millions of people worldwide to dictate messages, control devices, initiate searches or to facilitate data input in small devices. The user experience in these scenarios depends on the quality of the speech transcriptions and on the responsiveness of the system. For multilingual users, a further obstacle to natural interaction is the monolingual character of many ASR systems, in which users are constrained to a single preset language. In this work, we present an end-to-end multi-language ASR architecture, developed and deployed at Google, that allows users to select arbitrary combinations of spoken languages. We leverage recent advances in language identification and a novel method of real-time language selection to achieve similar recognition accuracy and nearly-identical latency characteristics as a monolingual system.
关键词： Automatic speech recognition (ASR),multilingual,deep neural network (DNN),language identification (LID)
更新于2025-09-23 15:21:01
-
[IEEE 2019 Compound Semiconductor Week (CSW) - Nara, Japan (2019.5.19-2019.5.23)] 2019 Compound Semiconductor Week (CSW) - Electric-field control of optical-spin injection from an InGaAs quantum well to p-doped quantum dots
摘要： Features for speech emotion recognition are usually dominated by the spectral magnitude information while they ignore the use of the phase spectrum because of the difficulty of properly interpreting it. Motivated by recent successes of phase-based features for speech processing, this paper investigates the effectiveness of phase information for whispered speech emotion recognition. We select two types of phase-based features (i. e., modified group delay features and all-pole group delay features), both which have shown wide applicability to all sorts of different speech analysis and are now studied in whispered speech emotion recognition. When exploiting these features, we propose a new speech emotion recognition framework, employing outer product in combination with power and L2 normalization. The according technique encodes any variable length sequence of the phase-based features into a fixed dimension vector regardless of the length of the input sequence. The resulting representation is fed to train a classification model with a linear kernel classifier. Experimental results on the Geneva Whispered Emotion Corpus database, including normal and whispered phonation, demonstrate the effectiveness of the proposed method when compared with other modern systems. It is also shown that, combining phase information with magnitude information could significantly improve performance over the common systems solely adopting magnitude information.
关键词： whispered speech emotion recognition,Phase-based features,outer product
更新于2025-09-23 15:21:01
-
[IEEE 2019 International Conference on Robotics and Automation in Industry (ICRAI) - Rawalpindi, Pakistan (2019.10.21-2019.10.22)] 2019 International Conference on Robotics and Automation in Industry (ICRAI) - Low Cost 2D Laser Scanner Based Indoor Mapping and Classification System
摘要： Although the field of automatic speaker or speech recognition has been extensively studied over the past decades, the lack of robustness has remained a major challenge. Feature warping is a promising approach and its effectiveness significantly depends on the relative positions of each of the features in a sliding window. However, the relative positions are changed due to the non-linear effect of noise. Aiming at the problem, this paper takes the advantage of ranking feature, which is obtained directly by sorting a feature sequence in descending order, to propose a method. It first labels the central frame in a sliding window as speech or noise dominant (‘‘reliable’’ or ‘‘unreliable’’). In the unreliable case, the ranking of the central frame is estimated. Subsequently, the estimated ranking is mapped to a warped feature using a desired target distribution for recognition experiments. Through the theoretical analysis and experimental results, it is found that autocorrelation of a ranking sequence is larger than that of the corresponding feature sequence. What is more, rank correlation is not easily influenced by abnormal data or data that are highly variable. Thus, this paper deals with a ranking sequence rather than a feature sequence. The proposed feature enhancement approach is evaluated in an open-set speaker recognition system. The experimental results show that it outperforms missing data method based on linear interpolation and feature warping in terms of recognition performance in all noise conditions. Furthermore, the method proposed here is a feature-based method, which may be combined with other technologies, such as model-based, scores-based, to enhance the robustness of speaker or speech recognition system.
关键词： Robustness,ranking feature,rank correlation,open-set speaker recognition,autocorrelation,feature warping,missing data method
更新于2025-09-23 15:21:01
-
[IEEE 2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE) - Aswan, Egypt (2020.2.8-2020.2.9)] 2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE) - Graphene AMC Array As A Ground Plane for Beam-Switching at Terahertz Band
摘要： Practically, no knowledge exists on the effects of speech coding and recognition for narrow-band transmission of speech signals within certain frequency ranges especially in relation to the recognition of paralinguistic cues in speech. We thus investigated the impact of narrow-band standard speech coders on the machine-based classification of affective vocalizations and clinical vocal recordings. In addition, we analyzed the effect of speech low-pass filtering by a set of different cut-off frequencies, either chosen as static values in the 0.5–5-kHz range or given dynamically by different upper limits from the first five speech formants (F1–F5). Speech coding and recognition were tested, first, according to short-term speaker states by using affective vocalizations as given by the Geneva Multimodal Emotion Portrayals. Second, in relation to long-term speaker traits, we tested vocal recording from clinical populations involving speech impairments as found in the Child Pathological Speech Database. We employ a large acoustic feature space derived from the Interspeech Computational Paralinguistics Challenge. Besides analysis of the sheer corruption outcome, we analyzed the potential of matched and multicondition training as opposed to miss-matched condition. In the results, first, multicondition and matched-condition training significantly increase performances as opposed to mismatched condition. Second, downgrades in classification accuracy occur, however, only at comparably severe levels of low-pass filtering. The downgrades especially appear for multi-categorical rather than for binary decisions. These can be dealt with reasonably by the alluded strategies.
关键词： Speech analysis,speech coding,emotion recognition,computational paralinguistics
更新于2025-09-23 15:21:01
-
Compact single-layer bandwidth-enhanced balanced bandpass filter using half-mode substrate-integrated waveguide
摘要： One particular challenge in biomedical named entity recognition (NER) and normalization is the identification and resolution of composite named entities, where a single span refers to more than one concept (e.g., BRCA1/2). Previous NER and normalization studies have either ignored composite mentions, used simple ad hoc rules, or only handled coordination ellipsis, making a robust approach for handling multitype composite mentions greatly needed. To this end, we propose a hybrid method integrating a machine-learning model with a pattern identification strategy to identify the individual components of each composite mention. Our method, which we have named SimConcept, is the first to systematically handle many types of composite mentions. The technique achieves high performance in identifying and resolving composite mentions for three key biological entities: genes (90.42% in F-measure), diseases (86.47% in F-measure), and chemicals (86.05% in F-measure). Furthermore, our results show that using our SimConcept method can subsequently improve the performance of gene and disease concept recognition and normalization. SimConcept is available for download at: http://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/SimConcept/
关键词： bioNLP,text mining,composite mentions,named entity recognition,coordination ellipsis
更新于2025-09-23 15:21:01
-
[IEEE 2019 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD) - Ottawa, ON, Canada (2019.7.8-2019.7.12)] 2019 International Conference on Numerical Simulation of Optoelectronic Devices (NUSOD) - Design and Modeling of 1 Gbps Directed Optical XOR/OR Gates Using Integrated Semiconductor Ring Lasers
摘要： In this paper, we formulate a novel time series representation framework that captures the inherent data dependency of time series and that can be easily incorporated into existing statistical classification algorithms. The impact of the proposed data representation stage in the solution to the generic underlying problem of time series classification is investigated. The proposed framework, which we call structural generative descriptions moves the structural time series representation to the probability domain, and hence is able to combine statistical and structural pattern recognition paradigms in a novel fashion. Two algorithm instantiations based on the proposed framework are developed. The algorithms are tested and compared using different publicly available real-world benchmark data. Results reported in this paper show the potential of the proposed representation framework, which in the experiments investigated, performs better or comparable to state-of-the-art time series description techniques.
关键词： structural generative descriptions (SGDs),time series representation,time series classification,Statistical-structural pattern recognition
更新于2025-09-23 15:21:01