Reviewerly/exHarmony huggingface dataset:
Visual Understanding through Natural Language

Author(s): Hendricks, Lisa Anne Marie | Advisor(s): Darrell, Trevor | Abstract: Powered by deep convolutional networks and large scale visual datasets, modern computer vision systems are capable of accurately recognizing thousands of visual categories. However, images contain much more than categorical labels: they contain information about where objects are located (in a forest or in a kitchen?), what attributes an object has (red or blue?), and how objects interact with other objects in a scene (is the child sitting on a sofa, or running in a field?). Natural language provides an efficient and intuitive way for visual systems to convey important information about a visual scene.We begin by considering a fundamental task as the intersection of language and vision: image captioning, in which a system receives an image as input and outputs a natural language sentence that describes the image. We consider two important shortcomings in modern image captioning models. First, in order to describe an object, like “otter”, captioning models require pairs of sentences and images which include the object “otter”. In Chapter 2, we build models that can learn an object like “otter” from classification data, which is abundant and easy to collect, then com- pose novel sentences at test time describing “otter”, without any “otter” image caption examples at train time. Second, visual description models can be heavily driven by biases found in the training dataset. This can lead to object hallucination in which models hallucinate objects not present in an image. In Chapter 3, we propose tools to analyze language bias through the lens of object hallucination. Language bias can also lead to bias amplification; e.g., if otters occur in 70% of train images, at test time a model might predict that otters occur in 85% of test images. We propose the Equalizer model in Chapter 4 to mitigate such bias in a special, yet important, case: gender bias.Moving on from captioning, we consider how systems which provide natural language text about an image can be used to help humans better understand an AI system. In Chapter 5, we propose to generate visual explanations with natural language, which rationalize the output of a deep visual classifier. We show these explanations can help humans understand when to accept or reject decisions made by an AI agent. Finally, in Chapter 6, we consider a new task at the intersection of language and vision: moment localization in videos with natural language. We detail the collection of a large scale dataset for this task, as well as the first models for moment localization.
Research in Service-Oriented Architecture with Cloud and SaaS Solutions

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Text Classification A Comparative Analysis of Word Embedding Algorithms

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
A Plea for Information Structure as a Part of Meaning Representation

The view that the representation of information structure (IS) should be a part of (any type of) representation of meaning is based on the fact that IS is a semantically relevant phenomenon (Sect.2.1).In the contribution, three arguments supporting this view are briefly summarized, namely, the relation of IS to the interpretation of negation and presupposition (Sect.2.2), the relevance of IS to the understanding of discourse connectivity and for the establishment and interpretation of coreference relations (Sect.2.3).A possible integration of the description of the main ingredients of IS into a meaning representation is illustrated in Section 3.
A regression-based algorithm for frequent itemsets mining

Purpose Frequent itemset mining (FIM) is a basic topic in data mining. Most FIM methods build itemset database containing all possible itemsets, and use predefined thresholds to determine whether an itemset is frequent. However, the algorithm has some deficiencies. It is more fit for discrete data rather than ordinal/continuous data, which may result in computational redundancy, and some of the results are difficult to be interpreted. The purpose of this paper is to shed light on this gap by proposing a new data mining method. Design/methodology/approach Regression pattern (RP) model will be introduced, in which the regression model and FIM method will be combined to solve the existing problems. Using a survey data of computer technology and software professional qualification examination, the multiple linear regression model is selected to mine associations between items. Findings Some interesting associations mined by the proposed algorithm and the results show that the proposed method can be applied in ordinal/continuous data mining area. The experiment of RP model shows that, compared to FIM, the computational redundancy decreased and the results contain more information. Research limitations/implications The proposed algorithm is designed for ordinal/continuous data and is expected to provide inspiration for data stream mining and unstructured data mining. Practical implications Compared to FIM, which mines associations between discrete items, RP model could mine associations between ordinal/continuous data sets. Importantly, RP model performs well in saving computational resource and mining meaningful associations. Originality/value The proposed algorithms provide a novelty view to define and mine association.
Frame Tone and Sentiment Analysis

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
A Low-power Real-time Hidden Markov Model Accelerator for Gesture User Interface on Wearable Devices

A low-power and real-time hidden Markov model (HMM) accelerator is proposed for gesture user interface on wearable smart devices. HMM algorithm is widely used for sequence recognition problems such as speech recognition and gesture recognition thanks to its best-in-class recognition accuracy. However, the HMM algorithm has high computational complexity and requires massive memory bandwidth in sequence matching process. Therefore, there have been studies on hardware acceleration of the HMM algorithm to resolve these issues, but they were focusing on the speech recognition and therefore did not accommodate the motion orientation function required for the gesture recognition problem. The motion orientation function computes the direction of hand movement in gesture sequence and thus involves compute intensive division and arctangent operations. In this paper, we propose an HMM accelerator with a light weight motion orientation module for realizing gesture recognition on wearable devices. Binary search method is exploited in the motion orientation module to avoid the division and arctangent operations associated with calculating orientations for reduced arithmetic complexity. In addition, gesture models are clustered in the gesture database to reduce external memory transactions. Moreover, logarithmic arithmetic is adopted in Viterbi decoder of the HMM algorithm for more reduction in its complexity. Thanks to these proposed schemes, this work achieves 25.6% power reduction compared with a vanilla hardware implementation of the gesture recognizing HMM.
Internet of Things based Waste Management System for Smart Cities A real time route optimization for waste collection vehicles

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
An Efficient Algorithm for Data Pre-Processing and Personalization in Web Usage Mining

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Natural Language Processing, Understanding, and Generation

The human brain is one of the most advanced machines when it comes to processing, understanding, and generating (P-U-G) natural language. The capabilities of the human brain stretch far beyond just being able to perform P-U-G on one language, dialect, accent, and conversational undertone. No machine has so far reached the human potential of performing all three tasks seamlessly. However, the advances in machine learning algorithms and computing power are making the distant dream of creating human-like bots a possibility.
Experiencias y lecciones aprendidas con el uso de metodologías de Design Thinking en cursos universitarios en el Ecuador

Ecuador is one of the countries, with an innovation index well below other nations in the region. There are many factors that influence this problem, one of them being the little capacity to generate new scientific knowledge that helps in the solution of problems in all productive processes or services. Universities are the pillars for the promotion and practice of innovation and creativity, through educational processes of teaching and learning. This research gathers the university experiences and achievements obtained in the learning, reached by the students and professors, who addressed the REDIMA study case and that constituted an opportunity to apply the Design Thinking methodology and that led us to devise and design solutions innovative to the problems raised.
Optimization in Feature Extraction schemes on Static Images to Improve the Performance of Automatic Facial Expression Recognition Systems

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Octonary (O) Search Algorithm

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Digital Image Compression Using Hybrid Technique based on DWT and DCT Transforms

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Exploring Methods for the Automatic Detection of Errors in Manual Transcription

Quality of data plays an important role in most deep learning tasks. In the speech community, transcription of speech recording is indispensable. Since the transcription is usually generated artificially, automatically finding errors in manual transcriptions not only saves time and labors but benefits the performance of tasks that need the training process. Inspired by the success of hybrid automatic speech recognition using both language model and acoustic model, two approaches of automatic error detection in the transcriptions have been explored in this work. Previous study using a biased language model approach, relying on a strong transcription-dependent language model, has been reviewed. In this work, we propose a novel acoustic model based approach, focusing on the phonetic sequence of speech. Both methods have been evaluated on a completely real dataset, which was originally transcribed with errors and strictly corrected manually afterwards.
Survey on Virtual Reality

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Label Distribution Learning Based Age-Invariant Face Recognition

Face recognition is an important application of computer vision. Al-though the accuracy of face recognition is high, face recognition and retrieval across age is still challenging. Faces across age can be very different caused by the aging process over time. The problem is that the images are not too similar, but with the same label. To reduce the intraclass discrepancy, in this paper we pro-pose a new method called Label Distribution learning for the end-to-end neural network to learn more discriminative features. Extensive experiments conducted on the three public domain face aging datasets (MORPH Album 2, CACD-VS and LFW) have shown the effectiveness of the proposed approach.
Web Pages of Engineering College Libraries in Andhra Pradesh: An Analysis

Web Technology is evolving more rapidly than the other technologies. The Internet already has a profound influence on institutes of higher education. Library websites of the institutions play an important role in the dissemination of information and library resources. It is very important to design any website carefully and systematically. It is also important to evaluate the websites before use. This study aims to evaluate and analyze the services, facilities and other information available on the library web pages of 246 engineering colleges in Andhra Pradesh which have library links on their web sites. An evaluation checklist is prepared based on previous studies.  The results of this study revealed that the majority of college library websites are providing information with regard to their collection, hours, and electronic resources. But there in a lack of update information, FAQs, web 2.0 applications, digital library and feedback facility.
An Efficient Approach for Sentiment Analysis Using Regression Analysis Technique

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Inclusion extraction from diamond clarity images based on the analysis of diamond optical properties

Diamond clarity refers to the absence of tiny, natural inclusions (imperfections) inside a diamond or on its surface. Almost all diamonds contain their own unique inclusions due to their natural formation process. In this paper, a new inclusion extraction approach is developed to accurately separate the regions of interest in a diamond clarity image and then identify the image features of each region. The inclusion regions can be successfully distinguished from other types of signals. The findings of the theoretical optical analysis facilitate the image processing development and also reduce its complexity and operation time. The experimental results verify the effectiveness and robustness of the proposed inclusion extraction approach. The diamond inclusions can be accurately extracted from the captured diamond clarity image. The extracted inclusions can also be converted to their actual size as seen by the naked human eye. The proposed approach is verified to be significantly less sensitive to noise than existing approaches and unaffected by the fluctuations in illumination.
Analysis the Breast Cancer using Back Propagation with Deep Neural Network

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.