检索结果-内蒙古大学图书馆

A Wide Learning Approach for Interpretable Feature Recommendation for 1-D Sensor Data in IoT Analytics

International Journal of Automation and computing 2019年第6期16卷 800-811页

作者： Snehasis Banerjee Tanushyam Chattopadhyay Utpal Garain TCS Research&Innovation Tata Consultancy ServicesEcospaceKolkata 700160India Computer Vision&Pattern Recognition Unit Indian Statistical Institute203 B.T.RoadKolkata 700108India

This paper presents a state of the art machine learning-based approach for automation of a varied class of Internet of things(Io T) analytics problems targeted on 1-dimensional(1-D) sensor data. As feature recommendation is a major bottleneck for general Io Tbased applications, this paper shows how this step can be successfully automated based on a Wide Learning architecture without sacrificing the decision-making accuracy, and thereby reducing the development time and the cost of hiring expensive resources for specific problems. Interpretation of meaningful features is another contribution of this research. Several data sets from different real-world applications are considered to realize the proof-of-concept. Results show that the interpretable feature recommendation techniques are quite effective for the problems at hand in terms of performance and drastic reduction in development time.

关键词： Feature engineering sensor data analysis Internet of things(IoT)analytics interpretable learning automation

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of a vision- and Grating-Sensor-Based Intelligent Unmanned Settlement System

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2022年第2期3卷 254-264页

作者： Zhang, Hong-Bo Zhou, Yi-Zhong Dong, Li-Jia Lei, Qing Du, Ji-Xiang Department of Computer Science and Technology Huaqiao University Xiamen361000 China Xiamen Key Laboratory of Computer Vision and Pattern Recognition The Fujian Key Laboratory of Big Data Intelligence and Security Huaqiao University Xiamen361000 China

In this article, a new vision- and grating-sensor-based intelligent unmanned settlement (IUS) system is proposed for convenience stores to automatically recognize the shopping behavior of customers, record their identities, and generate invoices. First, we design a new IUS architecture, which includes a shelf module and exit module. To achieve automatic settlement for each customer, a shopping event detection method is proposed. In this method, a vision-based human pose estimation algorithm is used to detect a human form standing in front of a shelf. The hand actions of each customer are detected by a grating sensor, and an image recognition method based on a convolutional neural network (CNN) is applied to recognize the items in the hands of customers. To reduce the image annotation workload, we propose a semisupervised training method for the recognition network. Based on hand action detection and item recognition, a shopping event recognition method is designed for the system, and a facial image of the customer corresponding to each shopping behavior is captured. Finally, each detected shopping event is added to the invoice of the corresponding customer via a facial recognition method. To verify the effectiveness of the proposed IUS system, we have built a handheld item image dataset and a shopping event dataset for an unmanned convenience store. The experimental results show that the proposed system can accurately recognize shopping behaviors and generate invoices. © 2020 IEEE.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Off-line handwritten Thai name recognition for student identification in an automated assessment system

Off-line handwritten Thai name recognition for student ident...

引用

2014 International Joint Conference on Neural Networks, IJCNN 2014

作者： Suwanwiwat, Hemmaphan Nguyen, Vu Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9781479914845

In the field of pattern recognition, off-line handwriting recognition is one of the most intensive areas of study. This paper proposes an automatic off-line Thai language student name identification system which was built as a part of a completed off-line automated assessment system. There is limited work undertaken in developing off-line automatic assessment systems using handwriting recognition. To the authors' knowledge, none of the work on the proposed system has been performed on the Thai language. In addition the proposed system recognises each Thai name by using an approach for whole word recognition, which is different from the work found in the literature as most perform character-based recognition. In this proposed system, the Gaussian Grid Feature (GGF) and the Modified Direction Feature (MDF) extraction techniques are investigated on upper and lower contours, loops from full word contour images of each name sample, and artificial neural networks and support vector machine are used as classifiers. The encouraging recognition rates for both feature extraction techniques were achieved when applied on loop, upper and lower contour images (99.27% accuracy rate was achieved using MDF on artificial neural networks and 99.27% using GGF with a support vector machine classifier). © 2014 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

On machine understanding of online handwritten mathematical expressions 7

On machine understanding of online handwritten mathematical ...

引用

7th International Conference on Document Analysis and recognition, ICDAR 2003

作者： Garain, Utpal Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata India

ISBN: (纸本)0769519601

This paper aims at automatic recognition of online handwritten mathematical expressions written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. A multiple-classifier consists of both parametric and nonparametric classifier has been used for recognition of symbols. Parametric classifier is based on Hidden Markov Model (HMM), whereas, non-parametric classifier uses Nearest Neighbor classification scheme. Structural analysis uses several online and offline features to identify the spatial relationships among symbols. A context free grammar has been designed to convert input expressions into their corresponding Latex strings. Contextual information has been used to correct several errors occurring at both recognition and structural analysis stage. A new method for evaluating performance of the proposed systems has been formulated. Experiments on a dataset of considerable size show high efficiency of the proposed system. © 2003 IEEE.

关键词： Structural analysis

来源：评论

学校读者我要写书评

暂无评论

A new multimodal sentiment analysis for images containing textual information

引用

Multimedia Tools and Applications 2024年 1-30页

作者： Ahuja, Garvit Alaei, Alireza Pal, Umapada School of Computer Science and Engineering Manipal University Jaipur Jaipur India Faculty of Science and Engineering Southern Cross University Gold Coast Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Multimodal sentiment analysis on images with textual content is a research area aiming to understand the sentiment conveyed by visual and textual elements in the images. While multimodal sentiment analysis on images and text (reviews) has its own challenges, the combination of textual and visual content in the form of images presents new challenges as well as opportunities. In this research work, we proposed a multimodal sentiment analysis method that works on images incorporating textual elements. In the textual sentiment analysis model, we initially employed a recognition system to extract textual data from input images. Our proposed multimodal method is based on transfer learning, considering two pre-trained deep learning models, Xception, and RoBERTa, to extract features from both visual and textual content from multimedia images. We then implemented a fusion strategy to combine these two modalities (Visual Sentiment Analysis (VSA) and Textual Sentiment Analysis (TSA)) to enhance the accuracy of the proposed method and to provide a more comprehensive understanding of sentiment in multimedia content. In addition, we curated a custom dataset comprising images with associated text labels and sentiments. To ensure accurate labels, we conducted human evaluations involving thirty annotators. Our dataset includes images labeled with negative, neutral, and positive sentiments. Experimental results demonstrated the effectiveness of combining visual and textual features for sentiment analysis. The findings from this research hold promising implications for real-world applications, such as sentiment analysis in social media, product reviews, and marketing campaigns, where both images and text play a significant role in conveying emotional context. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

A Simple Context Dependent Suggestion System 22

A Simple Context Dependent Suggestion System

引用

22nd Text REtrieval Conference, TREC 2013

作者： Roy, Dwaipayan Bandyopadhyay, Ayan Mitra, Mandar Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T.Road Kolkata700108 India

The Contextual Suggestion Problem focuses on search techniques for complex information needs that are highly dependent on context and user interest. In this paper, we present our approach to providing user and context dependent suggestions. The official evaluation scores for our submitted run are reported and compared to the overall median scores (across all 34 runs). © 2013 22nd Text REtrieval Conference, TREC 2013 - Proceedings. All Rights Reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Extraction of type style based meta-information from imaged documents 5

Extraction of type style based meta-information from imaged ...

引用

5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Garain, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 Barrackpore Trunk Road Calcutta700 035 India

ISBN: (纸本)0769503187

Extraction of some meta-information from printed documents without an OCR approach is considered. It can be statistically verified that important terms in articles are printed in italic, bold and all capital style. Detection of these type styles helps in automatic extraction of the lines containing titles, authors' names, subtitles, references as well as sentences having important terms occurring in the text. It also helps in improving the OCR performance for reading the italic text. Some experimental results on the performance of the approach on good quality as well as degraded document images are presented. © 1999 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Web Page Classification Algorithm Based on Semi-Supervised Support Vector Machine 2

Web Page Classification Algorithm Based on Semi-Supervised S...

引用

2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Huang, Wenqing You, Hui Zhejiang Sci-Tech University Institute of Computer Vision Image Processing and Pattern Recognition Acceptable School of Information Hangzhou China

ISBN: (纸本)9781538618035

Most web page classification algorithms are learning algorithms under the single-instance single-label framework. Multi-Instance Multi-Label learning is a new machine learning framework. MIMLSVM+ algorithm, using degenerate strategy to transform multiple instances into single instances, and then decomposing multiple labels into a series of two types of classification problems, that is, building an SVM for each label. Because the MIMLSVM+ algorithm degrades the multi-label problem into a series of two types of classification problems, the processing of each label will lose the contact information between the labels independently. Therefore, multi-tasking technology is introduced to make use of the multi-tasking learning framework based on nuclear to validate the MIMLSVM+ expand, get E-MIMLSVM+ algorithm. The paper improves E-MIMLSVM+ algorithm by using the semi-supervised learning method. Experimental results show that the proposed method can achieve higher classification accuracy. © 2018 IEEE.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

Building test collection from Old IR literature 14

Building test collection from Old IR literature

引用

6th International Workshop of the Forum for Information Retrieval Evaluation, FIRE 2014

作者： Chakraborty, Anirban Ghosh, Kripabandhu Parui, Swapan Kumar Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata700108 India

ISBN: (纸本)9781450337557

Standard test collections form the very basis of Information Retrieval research and evaluation. Important datasets have been created to promote empirical research and experimentation. In this paper, we describe our endeavour in creating a test collection from old, archived writings of IR stalwarts. The documents are created in text format from the scanned and OCRed version. The test collection consists of a set of documents in TREC format along with a set of expert queries and their relevance assessments. This dataset, though small in size, would be of paramount interest for researchers and students of IR since it contains valuable discourses on the discipline from its very inception. Also, to the best of our knowledge, no standard IR dataset has been built so far comprising old research articles. Furthermore, this is a dataset without the original error-free digital text version. So, the resulting collection would expect researchers to run retrieval experiments on the erroneous collection without the scope of error modeling. This would invite new research ideas. © 2015 ACM.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Low Resource Degraded Quality Document Image Binarization – Domain Adaptation is the Way 22

Low Resource Degraded Quality Document Image Binarization –...

引用

Proceedings of the Thirteenth Indian Conference on computer vision, Graphics and Image Processing

作者： Ahana Kundu Ujjwal Bhattacharya Computer Vision and Pattern Recognition Indian Statistical Institute IN Computer Vision and Pattern Recognition ISI Kolkata IN

ISBN: (纸本)9781450398220

Usually, image binarization plays a crucial role in automatic analysis of degraded documents from their captured images. However, this binarization task is often difficult due to a number of reasons including the high similarity between noisy background and faded foreground pixels. The study presented here is particularly focused on binarization of images of low-resource degraded quality documents based on a set of recently collected image samples of several rare, ancient and severely degraded quality printed documents of Bangla, the 2nd and 5th most popular script of India and the world respectively. This new collection of degraded document image samples will henceforth be referred as ’ISIDDI2’ and it consists of 139 images of Bangla old document pages. Samples of ’ISIDDI’, another existing database of degraded Bangla document image samples, have also been used in the present study. A novel deep architecture based on attention UNET++ with dilated convolution operation is proposed for this binarization task. The model is optimized using human vision perceptible distance reciprocal distortion (DRD) loss. Since the binarization ground truth of samples of both ’ISIDDI2’ and ’ISIDDI’ are not available, the proposed network has been trained using samples of DIBCO and H-DIBCO datasets and an unsupervised domain adaptation (DA) module is employed for adaptation of the proposed architecture to the degradation patterns of ’ISIDDI2’ or ’ISIDDI’ samples. The proposed binarization strategy includes certain post-processing operation based on a modified k-neighbourhood based approach for recovery of broken characters. Results of our extensive experimentation show that the proposed binarization strategy has improved the binarization output of state-of-the-art methods on both ISIDDI2 and ISIDDI datasets. Also, its performance on well-known DIBCO samples is satisfactory.

关键词： UNET++ degraded document image domain adaptation Image binarization attention

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：