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共 343 条记录，以下是51-60 订阅

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Semi-automatic Segmentation of Scattered and Distributed Objects 10th

Semi-automatic Segmentation of Scattered and Distributed Obj...

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10th international conference on Computer recognition Systems (CORES)

作者： Farid, Muhammad Shahid Lucenteforte, Maurizio Khan, Muhammad Hassan Grangetto, Marco Univ Punjab Coll Informat Technol Lahore Pakistan Univ Turin Dipartimento Informat Turin Italy Univ Siegen Pattern Recognit Grp Siegen Germany

ISBN: (纸本)9783319591629

this paper presents a novel object segmentation technique to extract objects that are potentially scattered or distributed over the whole image. the goal of the proposed approach is to achieve accurate segmentation with minimum and easy user assistance. the user provides input in the form of few mouse clicks on the target object which are used to characterize its statistical properties using Gaussian mixture model. this model determines the primary segmentation of the object which is refined by performing morphological operations to reduce the false positives. We observe that the boundary pixels of the target object are potentially misclassified. To obtain an accurate segmentation, we recast our objective as a graph partitioning problem which is solved using the graph cut technique. the proposed technique is tested on several images to segment various types of distributed objects e.g. fences, railings, flowers. We also show some remote sensing application examples, i.e. segmentation of roads, rivers, etc. from aerial images. the obtained results show the effectiveness of the proposed technique.

关键词： Object segmentation Gaussian mixturemodel Graph-cuts

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pattern recognition USING WIGNER DISTRIBUTION FUNCTION.

PATTERN RECOGNITION USING WIGNER DISTRIBUTION FUNCTION.

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10th international Optical computing conference.

作者： Vijaya Kumar, B.V.K. Carroll, Christopher

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Energy Efficient Speech Command recognition for Private Smart Home IoT Applications 10

Energy Efficient Speech Command Recognition for Private Smar...

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10th international conference on Modern Circuits and Systems Technologies (MOCAST)

作者： Zonios, Christos Tenentes, Vasileios Univ Ioannina Dept Comp Sci & Engn Ioannina Greece

ISBN: (纸本)9781665418478

Speech command recognition (SCR) services for smart homes rely on enterprise cloud servers and a fast internet connection. this negatively impacts service availability in offline use, and it raises privacy concerns in online use. the utilization of high computational resources on Internet-of-things (IoT) nodes and IoT gateways, allows for traditionally cloud-based services to be implemented closer to the end users. In this paper, we propose a SCR system that consists of an energy-efficient IoT node that communicates over a private BLE home network with an IoT gateway. Feature extraction on sound signals is performed on the IoT node, and speech command classification is performed on the IoT gateway using a novel deep neural network (DNN) model. We evaluate the DNN model accuracy of the proposed system using k-fold cross validation, and tune it based on the effect of different feature extraction parameters on the prediction accuracy, the IoT node energy consumption and system latency. the proposed system performs a task (sound acquisition, feature extraction, transmission and classification) with accuracy higher than 87.8%, latency similar to 1.136 sec, and consumes similar to 0.87 J of energy on the IoT node per task. the estimated system battery life is more than 422 days when performing a task per minute using a 3.7 V, 2000 mAh battery. the long-term battery life and the small footprint of the proposed system, make it ideal for cable-free discrete smart home installations and for wearable devices, while its offline availability reduces privacy concerns.

关键词： IoT speech command recognition edge computing microcontroller deep neural network

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Low Cost Outdoors WSN Parking System for Metropolitan Areas Based on RSS 10

Low Cost Outdoors WSN Parking System for Metropolitan Areas ...

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10th IEEE international conference on Intelligent Data Acquisition and Advanced computing Systems - Technology and Applications (IDAACS)

作者： Postigo-Malaga, Mauricio Porras Figueroa, Luis Chilo, Jose Univ Nacl San Agustin Arequipa Arequipa Peru Univ Gavle Gavle Sweden

ISBN: (纸本)9781728140698

Finding a free parking space in the metropolitan areas during rush hour is time consuming and it leads to traffic congestions and air pollution. Wireless Sensor Network (WSN) can be used to obtain information related to the parking condition requiring very little installation and maintenance costs. In this work, we present the design and implementation of an outdoor parking system based on Wireless Sensor Networks (WSNs), received signal strength (RSS) and pattern recognition algorithms to effectively find free parking spaces. Simulation and experiment results show good performance in the verification of the parking system. XBee-PRO 900HP-S3B modules with high performance and low power consumption were used. these modules support the IEEE-802.15.4 protocol for communication in the 900 MHz band and can be configured in different network topologies. the received signal strength (RSS) was measured to form fingerprints for the parking spaces availability (busy or vacant). Kalman filters were implemented to improve RSS which varies due to the effects of short-term fading. the parking spaces availability was evaluated with different classification algorithms in the WEKA environment with results up to 85%.

关键词： wireless sensor network fingerprints Kalman filter pattern recognition algorithms

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Multi-Scale Features Integration for Handwritten Mathematical Expression recognition 11

Multi-Scale Features Integration for Handwritten Mathematica...

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11th international conference on computing and pattern recognition, iccpr 2022

作者： Liu, Xianghao Wang, Da-Han Zhu, Shunzhi Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China

ISBN: (纸本)9781450397056

Handwritten mathematical expression recognition (HMER) is a challenging task due to the complex two-dimensional structure of mathematical expressions and the similarity of handwritten texts. Most existing methods for HMER only consider single-scale features while ignoring multi-scale features that are very important to HMER. Few works have explored the fusion of multi-scale features in HMER, but exhibited an extra branch that brings more parameters and computation. In this paper, we propose an end-to-end method to integrate multi-scale features using a unified model. Specifically, we customized the Dense Atrous Spatial Pyramid Pooling (DenseASPP) to our backbone network to capture the multi-scale features of the input image meanwhile expanding the receptive fields. Moreover, we added a symbol classifier using focal loss to better discriminate and recognize similar symbols, to further improve the performance of HMER. Experiments on the Competition on recognition of Online Handwritten Mathematical Expressions (CROHME) 2014, 2016 and 2019 shows that the proposed method achieves superior performance to most state-of-the-art methods, demonstrating the effectiveness of the proposed method. © 2022 ACM.

关键词： Character recognition

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Assessing pattern recognition Performance of Neuronal Cultures through Accurate Simulation 10

Assessing Pattern Recognition Performance of Neuronal Cultur...

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10th international IEEE-EMBS conference on Neural Engineering (NER)

作者： Lagani, Gabriele Mazziotti, Raffaele Falchi, Fabrizio Gennaro, Claudio Cicchini, Guido Marco Pizzorusso, Tommaso Cremisi, Federico Amato, Giuseppe Univ Pisa Dept Comp Sci Pisa Italy CNR Pisa Pisa Italy Univ Florence Dept Neurosci Florence Italy Scuola Normale Super Pisa Pisa Italy

ISBN: (纸本)9781728143378

Previous work has shown that it is possible to train neuronal cultures on Multi-Electrode Arrays (MEAs), to recognize very simple patterns. However, this work was mainly focused to demonstrate that it is possible to induce plasticity in cultures, rather than performing a rigorous assessment of their pattern recognition performance. In this paper, we address this gap by developing a methodology that allows us to assess the performance of neuronal cultures on a learning task. Specifically, we propose a digital model of the real cultured neuronal networks;we identify biologically plausible simulation parameters that allow us to reliably reproduce the behavior of real cultures;we use the simulated culture to perform handwritten digit recognition and rigorously evaluate its performance;we also show that it is possible to find improved simulation parameters for the specific task, which can guide the creation of real cultures.

关键词： Character recognition

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Raster map image analysis

Raster map image analysis

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ICDAR2009 - 10th international conference on Document Analysis and recognition

作者： Henderson, thomas C. Linton, Trevor School of Computing University of Utah Salt Lake City UT 84112 United States

ISBN: (纸本)9780769537252

Raster map images (e.g., USGS) provide much information in digital form;however, the color assignments and pixel labels leave many serious ambiguities. A color histogram classification scheme is described, followed by the application of a tensor voting method to classify linear features in the map as well as intersections in linear feature networks. the major result is an excellent segmentation of roads, and road intersections are detected with about 93% recall and 66 % precision. © 2009 IEEE.

关键词： Rasterization

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Geometric analysis and computing of projective structure and motion

Geometric analysis and computing of projective structure and...

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10th international conference on Image Analysis and Processing, ICIAP 1999

作者： Bayro-Corrochano, Eduardo Banarer, Vladimir Christian Albrechts University Computer Science Institute Preüsersträse 1-9 24105 Kiel Germany

ISBN: (纸本)0769500404

the paper focus on the analysis and computing of the projective structure and motion using geometric invariants. this work relates current approaches in the geometric algebra framework;as a result the approach gains geometric transparency and elegance. the paper presents experiments regarding projective reconstruction of shape and motion using both simulated and real images. © 1999 IEEE.

关键词： Geometry

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Proceedings - 2015 10th international conference on Broadband and Wireless computing, Communication and Applications, BWCCA 2015

Proceedings - 2015 10th International Conference on Broadban...

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10th international conference on Broadband and Wireless computing, Communication and Applications, BWCCA 2015

ISBN: (纸本)9781467383158

the proceedings contain 100 papers. the topics discussed include: data block management scheme based on secret sharing for HDFS;a new program classification method based on binary instrumentation and instruction flow feature extraction;a finite set network coding automatic repeat request scheme for machine-to-machine wireless broadcasting;distributed pattern transformation-invariant recognition scheme for real-time sensory applications;improved adaptive cooperative routing in underwater wireless sensor networks;selection of secure actors in wireless sensor and actor networks using fuzzy logic;the touchless person authentication using gesture-types emulation of handwritten signature templates;a simulation system based on ONE and SUMO simulators: performance evaluation of first contact, prophet and spray-and-wait DTN protocols;performance evaluation of different routing protocols in a vehicular delay tolerant network;and information security in intelligent data management processes.

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Social Risk and Depression: Evidence from Manual and Automatic Facial Expression Analysis

Social Risk and Depression: Evidence from Manual and Automat...

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10th IEEE international conference and Workshops on Automatic Face and Gesture recognition (FG)

作者： Girard, Jeffrey M. Cohn, Jeffrey F. Mahoor, Mohammad H. Mavadati, Seyedmohammad Rosenwald, Dean P. Univ Pittsburgh Dept Psychol Pittsburgh PA 15260 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Univ Denver Dept Elect & Comp Engn Denver CO 80208 USA

ISBN: (纸本)9781467355445;9781467355452

Investigated the relationship between change over time in severity of depression symptoms and facial expression. Depressed participants were followed over the course of treatment and video recorded during a series of clinical interviews. Facial expressions were analyzed from the video using both manual and automatic systems. Automatic and manual coding were highly consistent for FACS action units, and showed similar effects for change over time in depression severity. For both systems, when symptom severity was high, participants made more facial expressions associated with contempt, smiled less, and those smiles that occurred were more likely to be accompanied by facial actions associated with contempt. these results are consistent with the "social risk hypothesis" of depression. According to this hypothesis, when symptoms are severe, depressed participants withdraw from other people in order to protect themselves from anticipated rejection, scorn, and social exclusion. As their symptoms fade, participants send more signals indicating a willingness to affiliate. the finding that automatic facial expression analysis was both consistent with manual coding and produced the same pattern of depression effects suggests that automatic facial expression analysis may be ready for use in behavioral and clinical science.

关键词： behavioural sciences computing emotion recognition face recognition video signal processing

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