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Toward a Dual Attention Model for Image-Text Sentiment Classification 1

Toward a Dual Attention Model for Image-Text Sentiment Class...

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1st IEEE Afro-Mediterranean conference on Artificial Intelligence, AMCAI 2023

作者： Fatimi, Soukaina Sabbar, Wafae Bekkhoucha, Abdelkrim Mohammedia University Hassan II of Casablanca LIM Laboratory Faculty of Sciences and Techniques Mohammedia Morocco

ISBN: (纸本)9798350394689

Users are becoming accustomed to uploading text and pictures on social networks to express their feelings or ideas. As a result, multimodal sentiment analysis has drawn more attention as a study area in recent years. Nevertheless, most of the existing multimodal sentiment analysis approaches are focused either on emphasising the sentiment features in textual-visual data or on giving more importance to the correlation between texts and images. Motivated by this observation, we propose a dual attention model for image-text sentiment classification that focuses on both extracting attended visual and textual features relevant to the semantic classification, and uses the selected features to compute the correlation between the visual and textual data. Moreover, we take advantage of both the self-attention mechanism and the cross-modal mechanism to put in place a dual attention model for multimodal sentiment classification. The approach is carefully constructed and extensively explained, offering a strong theoretical base. The current research focuses on presenting a new theoretical method and its overall architecture. However, experimental validation is a crucial next step;a later article will present the experimental findings. © 2023 IEEE.

关键词： Sentiment analysis

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CAN SYNTHETIC data BOOST THE TRAINING OF DEEP ACOUSTIC VEHICLE COUNTING NETWORKS? 49

CAN SYNTHETIC DATA BOOST THE TRAINING OF DEEP ACOUSTIC VEHIC...

引用

49th IEEE International conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Damiano, Stefano Bondi, Luca Ghaffarzadegan, Shabnam Guntoro, Andre van Waterschoot, Toon Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS B-3001 Leuven Belgium Bosch Res Bosch Ctr Artificial Intelligence Gerlingen Germany

ISBN: (纸本)9798350344868;9798350344851

In the design of traffic monitoring solutions for optimizing the urban mobility infrastructure, acoustic vehicle counting models have received attention due to their cost effectiveness and energy efficiency. Although deep learning has proven effective for visual traffic monitoring, its use has not been thoroughly investigated in the audio domain, likely due to real-world data scarcity. In this work, we propose a novel approach to acoustic vehicle counting by developing: i) a traffic noise simulation framework to synthesize realistic vehicle pass-by events;ii) a strategy to mix synthetic and real data to train a deep-learning model for traffic counting. The proposed system is capable of simultaneously counting cars and commercial vehicles driving on a two-lane road, and identifying their direction of travel under moderate traffic density conditions. With only 24 hours of labeled real-world traffic noise, we are able to improve counting accuracy on real-world data from 63% to 88% for cars and from 86% to 94% for commercial vehicles.

关键词： acoustic vehicle counting synthetic data generation urban audio analysis

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visual Analytics of Learning Behavior Based on the Dendritic Neuron Model 17th

Visual Analytics of Learning Behavior Based on the Dendritic...

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17th International conference on Knowledge Science, Engineering and Management (KSEM)

作者： Tang, Cheng Chen, Li Li, Gen Minematsu, Tsubasa Okubo, Fumiya Taniguchi, Yuta Shimada, Atsushi Kyushu Univ Fac Informat Sci & Elect Engn Fukuoka 8190395 Japan Kyushu Univ Promot Off Data Driven Innovat Fukuoka 8190395 Japan Kyushu Univ Res Inst Informat Technol Fukuoka 8190395 Japan

ISBN: (纸本)9789819754946;9789819754953

Learning analytics, blending education theory, psychology, statistics, and computer science, utilizes data about learners and their environments to enhance education. Artificial Intelligence advances this field by personalizing learning and providing predictive insights. However, the opaque 'black box' nature of AI decision-making poses challenges to trust and understanding within educational settings. This paper presents a novel visual analytics method to predict whether a student is at risk of failing a course. The proposed method is based on a dendritic neuron model (DNM), which not only performs excellently in prediction, but also provides an intuitive visual presentation of the importance of learning behaviors. It is worth emphasizing that the proposed DNM has a better performance than recurrent neural network (RNN), long short term memory network (LSTM), gated recurrent unit (GRU), bidirectional long short term memory network (BiLSTM) and bidirectional gated recurrent unit (BiGRU). The powerful prediction performance can assist instructors in identifying students at risk of failing and performing early interventions. The importance analysis of learning behaviors can guide students in the development of learning plans.

关键词： visual analytics prediction learning behavior dendritic neuron model

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Research Hotspots and Development Trend of Blended Learning in China in the Past Two Decades: A Cite Space visual analysis Based on CSSCI Journal Literature 23

Research Hotspots and Development Trend of Blended Learning ...

引用

7th International conference on Education and Multimedia Technology, ICEMT 2023

作者： Zang, Wenjing School of Education Tianjin University China

ISBN: (纸本)9798400709142

In order to explore the research frontiers and hot topics of blended learning, the research on blended learning in China during the past two decades from 2004 to 2023 was visualized and analyzed with the help of CiteSpace, a software for visual metrics analysis, using CSSCI journals in the CNKI database as the source of data retrieval, and the method of bibliometric analysis and scientific knowledge mapping. The results of the study show that: (1) the current research on blended learning in China is rich in topics, but the cooperation between research authors is low, and the cohesion of research power is insufficient. (2) The research hotspots focus on the application of blended learning mode in flipped classroom, the practice of blended learning based on multiple teaching platforms, and the exploration of the integration of college English and blended learning. (3) In the future, the main trend of research will be to continue to carry out the theoretical study of blended learning, to explore the application of blended learning technology under the "Internet + technology", and to carry out the study of blended learning on the individual ability of students. CCS CONCEPTS: Applied computingĝ1/4Educationĝ1/4E-learning © 2023 ACM.

关键词： Engineering education

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NeuroPapyri: A Deep Attention Embedding Network for Handwritten Papyri Retrieval

NeuroPapyri: A Deep Attention Embedding Network for Handwrit...

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18th International conference on Document analysis and Recognition (ICDAR)

作者： De Gregorio, Giuseppe Perrin, Simon Pena, Rodrigo C. G. Marthot-Santaniello, Isabelle Mouchere, Harold Univ Basel Basel Switzerland Nantes Univ Lab Sci Numer Nantes LS2N Ecole Cent Nantes CNRSLS2NUMR 6004 F-44000 Nantes France

ISBN: (纸本)9783031706417;9783031706424

The intersection of computer vision and machine learning has emerged as a promising avenue for advancing historical research, facilitating a more profound exploration of our past. However, the application of machine learning approaches in historical palaeography is often met with criticism due to their perceived "black box" nature. In response to this challenge, we introduce NeuroPapyri, an innovative deep learning-based model specifically designed for the analysis of images containing ancient Greek papyri. To address concerns related to transparency and interpretability, the model incorporates an attention mechanism. This attention mechanism not only enhances the model's performance but also provides a visual representation of the image regions that significantly contribute to the decision-making process. Specifically calibrated for processing images of papyrus documents with lines of handwritten text, the model utilizes individual attention maps to inform the presence or absence of specific characters in the input image. This paper presents the NeuroPapyri model, including its architecture and training methodology. Results from the evaluation demonstrate NeuroPapyri's efficacy in document retrieval, showcasing its potential to advance the analysis of historical manuscripts.

关键词： Deep Learning Document Retrieval Historical Document analysis Handwriting Greek Papyri

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Affection: Learning Affective Explanations for Real-World visual data

Affection: Learning Affective Explanations for Real-World Vi...

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IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)

作者： Achlioptas, Panos Ovsjanikov, Maks Guibas, Leonidas Tulyakov, Sergey Snap Inc Santa Monica CA 90405 USA IP Paris Ecole Polytech LIX Paris France Stanford Univ Stanford CA USA

ISBN: (纸本)9798350301298

In this work, we explore the space of emotional reactions induced by real-world images. For this, we first introduce a large-scale dataset that contains both categorical emotional reactions and free-form textual explanations for 85,007 publicly available images, analyzed by 6,283 annotators who were asked to indicate and explain how and why they felt when observing a particular image, with a total of 526,749 responses. Although emotional reactions are subjective and sensitive to context (personal mood, social status, past experiences) - we show that there is significant common ground to capture emotional responses with a large support in the subject population. In light of this observation, we ask the following questions: i) Can we develop neural networks that provide plausible affective responses to real-world visual data explained with language? ii) Can we steer such methods towards producing explanations with varying degrees of pragmatic language, justifying different emotional reactions by grounding them in the visual stimulus? Finally, iii) How to evaluate the performance of such methods for this novel task? In this work, we take the first steps in addressing all of these questions, paving the way for more human-centric and emotionally-aware image analysis systems. Our code and data are publicly available at https://affective- ***.

关键词： datasets and evaluation

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ICMI 2024 - Proceedings of the 26th International conference on Multimodal Interaction

ICMI 2024 - Proceedings of the 26th International Conference...

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26th International conference on Multimodal Interaction, ICMI 2024

ISBN: (纸本)9798400704628

The proceedings contain 82 papers. The topics discussed include: LLM-powered multimodal insight summarization for UX testing;on multimodal emotion recognition for human-chatbot interaction in the wild;integrating multimodal affective signals for stress detection from audio-visual data;feeling textiles through AI: an exploration into multimodal language models and human perception alignment;decoding contact: automatic estimation of contact signatures in parent-infant free play interactions;ScentHaptics: augmenting the haptic experiences of digital mid-air textiles with scent;online multimodal end-of-turn prediction for three-party conversations;detecting deception in natural environments using incremental transfer learning;and exploring interlocutor gaze interactions in conversations based on functional spectrum analysis.

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VIVA: visual exploration and analysis of Videos with Interactive Annotation 28

VIVA: Visual Exploration and Analysis of Videos with Interac...

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28th Annual conference on Intelligent User Interfaces (IUI)

作者： Ruangrotsakun, Anita Oh, Dayeon Nguyen, Thuy-Vy Lee, Kristina Ser, Mark Hiew, Arthur Ngo, Rogers Shureih, Zeyad Khanna, Roli Kahng, Minsuk Oregon State Univ Corvallis OR 97331 USA Google Res Mountain View CA USA

ISBN: (纸本)9798400701078

This paper presents VIVA, a novel interactive tool for visually exploring long videos and searching for specific moments. Previous work on video data exploration and analytics often assumes that manually-created, rich annotations are available. However, such metadata may not be easily obtained. We design an interactively machine learning workflow for users to rapidly create annotations along a timeline. Combined with VIVA's focus+context visualization that effectively displays frame snapshots in the context of a video stream, VIVA enables users to explore and analyze long video clips by incrementally make sense of them. We present usage scenarios that demonstrate how users would use VIVA for video-related tasks.

关键词： visualization

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FitYou: A Personalized Dashboard for Health data 23

FitYou: A Personalized Dashboard for Health Data

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16th International Symposium on visual Information Communication and Interaction, VINCI 2023

作者： Zacheo, Giada Buzimkic, Amina La Roi, Andreas Van Schie, Alexander Staudt, Yves Burch, Michael Competence Centre for Data Analysis Visualisation and Simulation University of Applied Sciences Chur Switzerland

ISBN: (纸本)9798400707513

We introduce FitYou, an interactive dashboard for health data visualizations from wearable devices. It supports the exploration of health trends and health attribute correlations. Wearable devices are small enough to wear on the body and that can be equipped with sensors to track various physical and physiological attributes like heart rate, steps taken, and sleep quality, to just mention a few. By exploiting those attribute values we can visually monitor health-related issues, for example during sports activities like training, a sports competition, or a rehabilitation phase. Activity levels are hard to detect without such support but can help to improve someone's overall well-being. We illustrate the usefulness of FitYou by means of some application examples. Finally, we discuss the challenges and limitations of the dashboard by focusing on algorithmic, visual, and perceptual issues. © 2023 Owner/Author.

关键词： data visualization

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Geothermal Play Fairway analysis (GPFA) - Part ii: Texas/Gulf Coast Mechanisms of Heat Generation

Geothermal Play Fairway Analysis (GPFA) - Part II: Texas/Gul...

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2024 Geothermal Rising conference: Using the Earth to Save the Earth

作者： McCarthy, Kevin Pettitt, Will Priem, Rich Baker Hughes United States Priemere GeoTechnology United States

ISBN: (纸本)0934412308

Geothermal Play Fairway analysis (GPFA) is an exploration process adopted to geothermal, that integrates data of critical risk elements inherent to that specific geothermal play type. The key function of GPFA is to reduce risk and increase focus for improving exploration success rates. GPFA begins at the regional/basin scale, and progressively focuses in on the play scale. It then examines the critical risk element data to highlight which play areas have the highest likelihood of success (prospects). The outputs from the GPFA process are Common Risk Segment (CRS) & Composite Common Risk Segment (CCRS) Maps. CRS maps define areas that contain the same general Probability of Success (PoS) for each individual risk element based on the input data. Operator analyzed/ determined cutoff values or classes are then applied to each map with color assignments indicating high (red), medium (yellow) and low (green) risk areas for each element under consideration. Each individual CRS map is then composited into a single CCRS map. Publicly available data on hundreds of thousands of boreholes in Texas and the Gulf Coast demonstrate excellent potential for geothermal electricity generation from either current or abandoned oil and gas wells. Near-surface geothermal resources, at depths of 3 km (9,842 ft) or less, are generally less than 150°C (302°F) in Texas. Economically feasible electricity generation is possible with available subsurface temperature conditions within reasonable depths-generally greater than 120°C (248°F) within 4 km (13,123 ft) - given the prolific oil and gas well drilling. Extensive data exists to depths as much as 8 km (26,246 ft), indicating temperatures in excess of 300°C (572°F). When initiating an investigation into a new geothermal exploration area, a "high-level first pass" should be conducted for the heat resource before initiating the full GPFA process or detailed feasibility assessment. This is an important first step prior to conducting a detailed st

关键词： Geothermal prospecting

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