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Autonomous novel class discovery for vision-based recognition in non-interactive environments

Cognitive Robotics 2024年第1期4卷 191-203页

作者： Zhang, Xuelin Liu, Feng Cheng, Xuelian Yan, Siyuan Liao, Zhibin Ge, Zongyuan Faculty of Information Technology Monash University 20 Exhibition Walk MelbourneVIC3168 Australia The School of Computing and Information Systems The University of Melbourne Parkville MelbourneVIC3052 Australia Faculty of Sciences Engineering and Technology The University of Adelaide North Terrace Adelaide SA5001 Australia

Visual recognition with deep learning has recently been shown to be effective in robotic vision. However, these algorithms tend to be build under fixed and structured environment, which is rarely the case in real life. When facing unknown objects, avoidance or human interactions are required, which may miss critical objects or be prohibitively costly to obtain on robots in the real world. We consider a practical problem setting that aims to allow robots to automatically discover novel classes with only labelled known class samples in hand, defined as open-set clustering (OSC). To address the OSC problem, we propose a framework combining three approaches: 1) using selfsupervised vision transformers to mitigate the discard of information needed for clustering unknown classes;2) adaptive weighting for image patches to prioritize patches with richer textures;and 3) incorporating a temperature scaling strategy to generate more separable feature embeddings for clustering. We demonstrate the efficacy of our approach in six fine-grained image datasets. © 2024 The Authors

关键词： Machine vision

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Transformer-based models for multimodal irony detection

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Journal of Ambient Intelligence and Humanized computing 2023年第6期14卷 7399-7410页

作者： Tomás, David Ortega-Bueno, Reynier Zhang, Guobiao Rosso, Paolo Schifanella, Rossano Department of Software and Computing Systems University of Alicante Alicante Spain PRHLT Research Center Universitat Politècnica de València Valencia Spain School of Information Management Wuhan University Wuhan China Applied Research on Computational Complex Systems University of Turin Turin Italy

Irony is nowadays a pervasive phenomenon in social networks. The multimodal functionalities of these platforms (i.e., the possibility to attach audio, video, and images to textual information) are increasingly leading their users to employ combinations of information in different formats to express their ironic thoughts. The present work focuses on the study of irony detection in social media posts involving image and text. To this end, a transformer architecture for the fusion of textual and image information is proposed. The model leverages disentangled text attention with visual transformers, improving F1-score up to 9% over previous existing works in the field and current state-of-the-art visio-linguistic transformers. The proposed architecture was evaluated in three different multimodal datasets gathered from Twitter and Tumblr. The results revealed that, in many situations, the text-only version of the architecture was able to capture the ironic nature of the message without using visual information. This phenomenon was further analysed, leading to the identification of linguistic patterns that could provide the context necessary for irony detection without the need for additional visual information. © 2022, The Author(s).

关键词： Architecture

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Integrating Data Protection at Interface of RISC-V Processor Core

Integrating Data Protection at Interface of RISC-V Processor...

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2024 Panhellenic Conference on Electronics and Telecommunications, PACET 2024

作者： Mach, Jan Kohutka, Lukas Cicak, Pavel Slovak University of Technology Institute of Computer Engineering and Applied Informatics Slovakia Information Systems and Software Engineering Slovak University of Technology Institute of Informatics Slovakia

ISBN: (纸本)9798350318845

Fulfilling increasing performance demands of space and automotive applications can be problematic as high dependability is required. Memory is one of the most radiationsensitive parts, so it is often protected with information redundancy. This paper describes an integration of error correction and detection techniques into the interface of RISC-V processor to protect the data stored in the memory. We also provide a hardware-software interface for reporting errors and software routines for correcting data in memory. Our solution has a negligible impact (-3.9%) on the overall performance of the core with a small area and power consumption overhead. © 2024 IEEE.

关键词： Error correction

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Deep Learning Based Face Mask Detection in Religious Mass Gathering During COVID-19 Pandemic

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Computer systems Science & Engineering 2023年第8期46卷 1863-1877页

作者： Abdullah S AL-Malaise AL-Ghamdi Sultanah MAlshammari Mahmoud Ragab Information Systems Department Faculty of Computing and Information Technology King Abdulaziz UniversityJeddah21589Saudi Arabia Information Systems Department HECI SchoolDar Alhekma UniversityJeddahSaudi Arabia Center of Excellence in Smart Environment Research King Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Mathematics Faculty of ScienceAl-Azhar UniversityNaser CityCairo11884Egypt

Notwithstanding the religious intention of billions of devotees,the religious mass gathering increased major public health concerns since it likely became a huge super spreading event for the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).Most attendees ignored preventive measures,namely maintaining physical distance,practising hand hygiene,and wearing *** a face mask in public areas protects people from spreading *** intelligence(AI)based on deep learning(DL)and machine learning(ML)could assist in fighting covid-19 in several *** study introduces a new deep learning-based Face Mask Detection in Religious Mass Gathering(DLFMD-RMG)technique during the COVID-19 *** DLFMD-RMG technique focuses mainly on detecting face masks in a religious mass *** accomplish this,the presented DLFMD-RMG technique undergoes two pre-processing levels:Bilateral Filtering(BF)and Contrast *** face detection,the DLFMD-RMG technique uses YOLOv5 with a ResNet-50 *** addition,the face detection performance can be improved by the seeker optimization algorithm(SOA)for tuning the hyperparameter of the ResNet-50 module,showing the novelty of the *** last,the faces with and without masks are classified using the Fuzzy Neural Network(FNN)*** stimulation study of the DLFMD-RMG algorithm is examined on a benchmark *** results highlighted the remarkable performance of the DLFMD-RMG model algorithm in other recent approaches.

关键词： Religious mass gathering Hajj and Umrah covid-19 pandemic face mask computer vision deep learning

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Chlorophyll-based Saturable Absorber for Q-switched Pulse Generation in Er-Doped Fiber Laser Cavity 10

Chlorophyll-based Saturable Absorber for Q-switched Pulse Ge...

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10th IEEE International Conference on Photonics, ICP 2024

作者： Tarmizi, S.Z.A. Ahmad Mansor, M. Abidin, N.H. Zainol Mahdi, M.A. Mazlan, M.F. Computer and Communication Systems Engineering Universiti Putra Malaysia Selangor UPM Serdang 43400 Malaysia Department of Computing and Information Systems School of Engineering and Technology Sunway University Selangor 47500 Malaysia

ISBN: (纸本)9798350383164

In this paper, we present experimental results on the use of all-organic Chlorophyll-based saturable absorber (Chl-SA) extracted from spinach for the generation of Q- switched pulse. The Chl-SA was fabricated by depositing Chl in powder form onto a fiber ferrule. The Chl-SA generated Q- switched pulse at 1559-1560 nm when employed in a 980 nm laser diode pumped erbium-doped fiber laser (EDFL) cavity. Pulse generation was achieved from 45 mW pump power up to 70 mW pump powers where the repetition rate increased while pulse duration shortened with increasing pump power. The highest repetition rate of 15.15 kHz and shortest pulse width of 32 µs were obtained. This highlights the promising potential of chlorophyll as a standalone material and its capacity to potentially boost the generation of pulse lasers when combined with other materials. ©2024 IEEE.

关键词： Pulse repetition rate

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Enhancing SEO Compliance of JavaScript Web Frameworks through Automated Testing inside CI/CD Pipelines 11

Enhancing SEO Compliance of JavaScript Web Frameworks throug...

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11th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2024

作者： Ágh, Ján Makarova, Irina Dakić, Pavle Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava842 16 Slovakia Faculty of Informatics and Computing Singidunum University Danijelova 32 Belgrade Serbia

This article aims to incorporate search engine optimization validation into the development process of JavaScript-based web applications, thus connecting two sides of optimizations, namely the selection of appropriate practices and their correct implementation. We summarize strategies for achieving search engine optimization (SEO) compliance in single-page applications (SPAs) and propose two distinct testing solutions aimed at addressing SEO concerns in modern web apps. Both approaches are incorporated into CI/CD pipelines, making it possible to enforce existing SEO strategies. The issue of visibility in search engines is especially characteristic for JavaScript-based frameworks. This is because of the way they load and render their content, are mostly unable to achieve satisfactory SEO scores and rankings. Due to the ever-increasing popularity of these frameworks, it is essential to identify and compare available optimization techniques to address this subject adequately. Here, we take a closer look at the SEO-friendly features of *** and *** frameworks and evaluate their capabilities using two mock e-commerce websites as examples. To fulfill our second objective, an approach to continuous SEO testing is presented. We discuss the results of similar CI/CD pipeline setups using distinct technologies and tools, in particular Jenkins and GitHub actions. The results show that by integrating specific tests focused on SEO into CI/CD pipelines, developers can identify crucial shortcomings of their product and eliminate them before they cause harm in the production environment. © 2024 Copyright for this paper by its authors.

关键词： Search engines

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Hybrid Transfer Learning Approach for Emotion Analysis of Occluded Facial Expressions 6th

Hybrid Transfer Learning Approach for Emotion Analysis of ...

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6th International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2023

作者： Pamod, Dilshan Charles, Joseph Hewarathna, Ashen Iranga Vigneshwaran, Palanisamy Lekamge, Sugeeswari Thuseethan, Selvarajah Department of Computing and Information Systems Sabaragamuwa University of Sri Lanka Belihuloya Sri Lanka Erlangen Germany Department of Software Engineering Sabaragamuwa University of Sri Lanka Belihuloya Sri Lanka School of Information Technology Deakin University Geelong Australia

ISBN: (纸本)9783031530814

The ability to recognise and interpret emotional expressions is crucial since emotions play a significant role in our daily lives. Emotions are multifaceted phenomena that affect our behavior, perception, and cognition. As a result, numerous machine-learning and deep-learning algorithms for emotion analysis have been studied in previous works. Finding emotion in an obscured face, such as one covered by a scarf or hidden in shadow, is considerably harder than in a complete face, though. This study explores the effectiveness of deep learning models in occluded facial emotion analysis through a transfer learning approach. The performance of two individual pre-trained models, MobileNetV2 and EfficientNetB3, is compared alongside a hybrid model that combines both approaches. This comparison is conducted using the FER-2013 dataset. The dataset consists of 35,887 images and categorizes emotions into seven emotional categories. The results indicate that the hybrid model attained the highest accuracy, with a score of 93.04% for faces occluded at the top and 92.63% for faces occluded at the bottom. Additionally, the study suggests that top-occluded faces displayed more pronounced emotional expressions in comparison to bottom-occluded faces. Overall, these findings imply that hybrid architecture, which was developed as a state-of-the-art model in the study, proves to be effective for analyzing emotions in facial expressions that are partially obscured. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Learning algorithms

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Student Placement Prediction Using Machine Learning Algorithms

Student Placement Prediction Using Machine Learning Algorith...

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2023 Innovations in Power and Advanced computing Technologies, i-PACT 2023

作者： Aruna, P. Abinayashri, V.S. Abinayaa Sree, K.S. Meghashri, A. Department of Computing Coimbatore Institute of Technology Coimbatore India M.Sc. Software Systems Coimbatore Institute of Technology Coimbatore India

ISBN: (纸本)9798350325188

The student placement prediction plays a crucial role in modern educational institutions and the job market. To make informed decisions with machine learning algorithms, accurate placement prediction has become achievable. This model focuses on the application of machine learning algorithms for placement prediction, analyzing their effectiveness, and comparing their performance. Educational institutions that facilitate this process can identify areas of improvement in their curriculum and career counseling services, leading to better student outcomes and satisfaction. To save time and resources for companies, it helps optimize their hiring process. This model also focuses on the implementation of machine learning algorithms that can accurately predict whether a student will be placed or not, based on a set of input features such as academic scores, internship experience, activities, and more. This model supports other machine learning algorithms. It provides valuable insights into student employability factors and contributes to fostering a better future for both students and the job market. However, updating the model with fresh data and refinement ensures its accuracy and relevance in an ever-changing job landscape. © 2023 IEEE.

关键词： Classification Gradient Boosting Neural Network Random Forest

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A Decision Support System for Enhancing Transportation Services Using Aspect-Based Sentiment Analysis

A Decision Support System for Enhancing Transportation Servi...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Benaddi, Lamya Ouaddi, Charaf Naimi, Lahbib Souha, Adnane Jakimi, Abdeslam Ouchao, Brahim Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Science and Technology Errachidia Department of Computer Sciences Morocco

ISBN: (纸本)9798350369106

This paper proposes an innovative decision support system based on sentiment analysis, specifically designed for the transportation sector. The system employs an aspect-based sentiment analysis approach, which accurately identifies and classifies customer opinions on key transportation service aspects such as comfort, driver behavior, punctuality, and vehicle condition. By integrating the BERT model, known for its advanced natural language processing capabilities, our system provides an in-depth and reliable analysis of customer sentiments. This analysis enables managers and decision-makers to better understand the strengths and weaknesses of the provided transportation services and to precisely target areas that require improvement. By offering actionable insights, our approach aims to enhance the user experience, improve service quality, and increase overall customer satisfaction. © 2024 IEEE.

关键词： Customer satisfaction

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Intelligent Daycare: Enhancing Child Safety with IoT and Machine Learning Innovations 9

Intelligent Daycare: Enhancing Child Safety with IoT and Mac...

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9th International Conference on Communication and Electronics systems, ICCES 2024

作者： Prathyanga, Amisha Shyaminda, Pasindu Chamikara, Pasan Lakshan, Sachin Thelijjagoda, Samantha Kasthurirathna, Dharshana Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798350377972

Child safety and well-being in daycare settings are important, thus it is vital that the persons in charge be attentive to them. This research tries to solve the problem by introducing a smart and detailed monitoring system that utilizes new technology to enhance safety and support caretakers. The system has various innovative features, such as child missing detection, behavior and facial expression analysis, cry analysis and categorization, and fall detection. Using high-resolution cameras and on-device Edge AI capabilities, it ensures real-time surveillance of children's activities while protecting privacy. The approach integrates behavior and facial expression analysis to assess emotional states, cry recognition to discover childcare needs, as well as a useful fall detection system that can tell the difference between falls and other movements. All these parts synergize to hand over the necessary information to the caregivers on time and in a way that they can act upon. The quantitative experiments in real-time childcare centers show high accuracy through all the components, attesting to the system's reliability and durability. This research has important significance in improving the safety and the frequency response in daycare centers because it gives caregivers automated tools to quickly address the needs of children. While promising, the system has drawbacks, such as potential biases in data models and a reliance on ideal environmental circumstances. Future work intends to improve flexibility across varied daycare situations, improve accuracy through larger datasets, and investigate ethical frameworks for wider application. © 2024 IEEE.

关键词： Fall detection

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