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检索条件"任意字段=2021 13th International Conference on Machine Learning and Computing, ICMLC 2021"

共 633 条记录，以下是11-20 订阅

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Improving Multilingual Temporal Answering Grounding in Single Video via LLM-Based Translation and OCR Enhancement 13th

Improving Multilingual Temporal Answering Grounding in Singl...

引用

13th international conference on Natural Language Processing and Chinese computing

作者： Zhang, Huan Zheng, Chen He, Yuanjing Zhao, Yan Lai, Yuxuan Open Univ China Beijing Peoples R China Minist Educ Engn Res Ctr Integrat & Applicat Digital Learning Beijing Peoples R China

ISBN: (纸本)9789819794423;9789819794430

In the digital age, the widespread preference for instructional videos as an educational aid demands cutting-edge technologies that can swiftly pinpoint video segments in response to queries. In light of the likelihood that learners from various cultural backgrounds may pose questions in different languages, the multilingual temporal answer grounding in single video (mTAGSV) challenge has been introduced. MTAGSV requires models to precisely identify the particular time segment within the video that align with the query posed in Chinese or English. By addressing the limitations of existing monolingual approaches and their inefficacy with silent videos, we utilize optical character recognition (OCR) to enhance video information and leverage large language models (LLMs) to bridge linguistic gap. For videos that contain audio, the subtitles are extracted by an automated speech recognition (ASR) tool. For silent videos or those with insufficient audio-based subtitles, we leverage an OCR tool to extract textual content from video frames, refining the OCR-generated text to act as a surrogate for subtitles. Furthermore, we leverage LLMs to translate English queries into their Chinese equivalents, bridging the linguistic divide between queries and video contents. the MutualSL model is employed as the backbone network for extracting features from textual subtitles and visual frames. through extensive experiments, we demonstrate that our proposed techniques enhance the task performance, securing first place in track 1 of NLPCC 2024 shared task 7.

关键词： Temporal Video Grounding Multilingual Task Large Language Model OCR

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Towards A Lightweight Deep learning Framework for Real-Time Vital Sign Prediction with RGB Cameras 13

Towards A Lightweight Deep Learning Framework for Real-Time ...

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13th international Winter conference on Brain-Computer Interface, BCI 2025

作者： Kim, Seong-Wook Park, Hyeong-Yeong Lee, In-Gyu Jang, Se-Na Yu, Seong-Hyun Oh, Jun-Young Moon, Gee-Myung Jeong, Ji-Hoon Dept. Computer Science Chungbuk National University Cheongju Korea Republic of injewelme Co. Ltd. Seoul Korea Republic of

ISBN: (纸本)9798331521929

Remote photoplethysmography (rPPG) is a technology that extracts blood volume pulse (BVP) signals by analyzing the wavelength differences of light reflected from a person’s skin using devices such as RGB and infrared cameras. this technology enables the measurement and estimation of various physiological signals, including heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory rate, and oxygen saturation. In this study, we overcame the limitations of existing rPPG methods by constructing a custom RGB-rPPG dataset. the dataset was collected from 14 subjects using an RGB camera (a standard webcam), wearable device, and sphygmomanometer. the leave-one-subject-out (LOSO) approach was applied for model training to predict SBP and DBP, while HR was estimated using a fast Fourier transform (FFT). the average mean absolute error for SBP/DBP prediction and HR estimation were 4.55 (±2.7660) mmHg, 1.84 (±1.6064) mmHg, and 6.91 (±8.0319) bpm, respectively. these results demonstrate that the constructed RGB-rPPG dataset and the proposed method are effective for predicting physiological signs. © 2025 IEEE.

关键词： Blood pressure

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Effectiveness of Transfer learning in Autonomous Driving using Model Car 2021

Effectiveness of Transfer Learning in Autonomous Driving usi...

引用

2021 13th international conference on machine learning and computing, icmlc 2021

作者： Chiba, Shohei Sasaoka, Hisayuki Asahikawa Japan Asahikawa Japan

ISBN: (纸本)9781450389310

We have known that reinforcement learning, deep learning, and deep reinforcement learning effectively acquire action rules for the autonomous motion of objects. However, it is known that these learning processes require a large amount of learning time. Besides, we should consider the similarity of the environment between the training target and the test target. In actual autonomous driving, there is no such thing as driving only on a course that has been learned in advance. In this study, the autonomous driving of a model car is used as the experimental object. the training target for acquiring the learning model and the actual driving courses are changed. In this study, we report on the effectiveness of transfer learning using a model car as the basis for a learning model acquired by reinforcement learning. © 2021 ACM.

关键词： Deep learning

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Ensemble learning in Stock Market Prediction 2021

Ensemble Learning in Stock Market Prediction

引用

2021 13th international conference on machine learning and computing, icmlc 2021

作者： Ezzeddine, Hassan R. Achkar, Roger Department of Computer and Communications Engineering Faculty of Engineering American University of Science and Technology Beirut Lebanon Lebanon

ISBN: (纸本)9781450389310

In recent years, the increasing influence of machine learning in different industries had inspired many traders to benefit from it in the world of finance, stock trading is one of the most important activities. Predicting the direction of stock prices is a widely studied subject in many fields including trading, finance, statistics and computer science. the main concern for Investors is to maximize their profit if they determine when to buy/sell an investment they apply Analytical methods that makes use of different sources ranging from news to price data, all aiming at predicting the company's future stock price ML applications have presented investors with something new. A combination of technologies that could entirely reshape the way they make investment decisions. the purpose of this thesis is to leverage the aggregation of technical, fundamental, and sentiment analysis with stacked machine learning models capable of predicting profitable actions to be executed. © 2021 ACM.

关键词： Sentiment analysis

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DSP-PIGAN: A Precision-Consistency machine learning Algorithm for Solving Partial Differential Equations 2021

DSP-PIGAN: A Precision-Consistency Machine Learning Algorith...

引用

2021 13th international conference on machine learning and computing, icmlc 2021

作者： Wang, Yunzhuo Sun, Hao Sun, Guangzhong University of Science and Technology of China Hefei China

ISBN: (纸本)9781450389310

Partial differential equations (PDEs) are the most ubiquitous tool for modeling problems in nature. In recent years, machine learning techniques are adopted to solve PDEs. However, the prediction errors of existing machine learning methods vary widely on different subdomains of PDEs. How to achieve precision-consistency is a crucial and complex issue for machine learning methods for solving PDEs. To tackle this issue, we propose DSP, an adaptive framework for solving PDEs. DSP is composed of domain decomposition, searching for singular subdomains, and prediction. Furthermore, a novel generative model, physics-informed generative adversarial network (PIGAN), is designed to solve PDEs. In addition, we introduce points with high-precision labels into the training process of the model to improve model accuracy. We test the effectiveness of our approach on three real physical equations: Poisson equation, Helmhotz equation and Eikonal equation. through experiments, we prove that the combination of DSP and PIGAN outperforms various state-of-the-art baselines. © 2021 ACM.

关键词： learning algorithms

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Active learning for Concept Prerequisite learning in Wikipedia 2021

Active Learning for Concept Prerequisite Learning in Wikiped...

引用

2021 13th international conference on machine learning and computing, icmlc 2021

作者： Hu, Xinying He, Yu Sun, Guangzhong University of Science and Technology of China Anhui Hefei China

ISBN: (纸本)9781450389310

the prerequisite relationship of the concept plays an important role in education. Previously, the prerequisites were given by experts, which is very costly. With the development of the Internet, many new concepts have emerged. And there are a growing number of electronic materials available. In this case, it's important to produce an efficient and accessible prerequisite annotator that is beneficial to make an efficient learning plan. this paper proposes a method to mine prerequisite relationships of concepts from Wikipedia by using active learning, which can use fewer artificial labels to obtain an accurate model. the proposed method extracts features from Wikipedia articles, and designs a new active learning algorithm based on the characteristics of concept prerequisites. Experimental results show that the proposed model outperforms existing active learning methods for concept prerequisite learning. © 2021 ACM.

关键词： learning systems

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Bird Songs Recognition Based on Ensemble Extreme learning machine 2021

Bird Songs Recognition Based on Ensemble Extreme Learning Ma...

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2021 13th international conference on machine learning and computing, icmlc 2021

作者： Xie, Shanshan Xu, Haifeng Liu, Jiang Zhang, Yan Lv, Danjv College of Big Data and Intelligence Engineering Southwest Forestry University China

ISBN: (纸本)9781450389310

ELM (Extreme learning machine) is a random method for Single-hidden layer feedforward neural network construction, and MFCC (Mel-frequency Cepstrum Coefficient) is a kind of feature parameter for speech recognition. Based on Ensemble ELM research on bird songs recognition technology, this paper firstly preprocesses the bird songs data collected by web crawler, then extracts MFCC feature parameters from the songs data, and gets the improved MFCC feature parameters through differential calculation. Finally, Ensemble ELM is used for bird songs classification and recognition. the experimental results show that the Ensemble ELM method can achieve a recognition rate of 90.42% in the classification of 10 kinds of birds. © 2021 ACM.

关键词： Birds

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Using Deep learning to Construct Auto Web Penetration Test 2021

Using Deep Learning to Construct Auto Web Penetration Test

引用

2021 13th international conference on machine learning and computing, icmlc 2021

作者： Jiao, Jian Zhao, Haini Cao, Hongsheng Beijing Information Science and Technology University China

ISBN: (纸本)9781450389310

Penetration test is an important means to test the security of the web system. It has been mainly carried out by tester manually. the main reason is that it is difficult to generate test path and code automatically because of the complex network environment. the traditional method for attack path can't give the code for the whole penetration process. the traditional penetration path is based on the correlation between vulnerabilities and lacks practical experience support. In this paper, we propose a method based on CNN, which can automatically produce the code of penetration test by training the data which originate from the real attack events. We further implement the system to verify it. In a real environment experiment, we have validated the system, and analyzed the feasibility and performance of the CNN technology for penetration tests. © 2021 ACM.

关键词： Complex networks

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Deploying Collaborative machine learning Systems in Edge with Multiple Cameras 13

Deploying Collaborative Machine Learning Systems in Edge wit...

引用

13th international conference on Mobile computing and Ubiquitous Network (ICMU)

作者： Jang, Si Young Acer, Utku Gunay Min, Chulhong Kawsar, Fahim Korea Adv Inst Sci & Technol Daejeon South Korea Nokia Bell Labs Antwerp Belgium Nokia Bell Labs Cambridge England

ISBN: (纸本)9784907626488

Advancement in hardware capability has opened up the possibility of performing ML inference tasks at the edge using a large volume of sensory data generated from IoT devices such as cameras. As cameras become more pervasive, edge systems need to process streams from multiple sources with overlapping fields-of-view. In this position paper, we describe a collaborative sensing mechanism at the edge for such cases. We introduce a View Mapping Database (DB) that maps regions in a camera's field of view to regions in other cameras' view. We analyze characteristics of 5 video streams that capture an intersection from multiple angles, prototype a View Mapping DB, and present our preliminary results.

关键词： Performance evaluation Collaboration Prototypes machine learning Streaming media Cameras Hardware

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RULE ACQUISITION BASED ON MULTI-LEVEL COGNITIVE learning IN MULTI-DECISION DATA 20

RULE ACQUISITION BASED ON MULTI-LEVEL COGNITIVE LEARNING IN ...

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20th international conference on machine learning and Cybernetics (icmlc)

作者： Fan, Bing-Jiao Li, Guo-Cheng Tsang, Eric-C C. Li, Wen-Tao Beijing Informat Sci & Technol Univ Sch Appl Sci Beijing 100096 Peoples R China Macau Univ Sci & Technol Fac Informat Technol Taipa Macao Peoples R China Southwest Univ Coll Artificial Intelligence Chongqing 400715 Peoples R China

ISBN: (纸本)9781665466080

In this paper, we defined the decision rule in multi-decision data from the perspective of multi-level cognitive concept learning. Compared with the decision rule based on rough set theory, we proved that the proposed decision rule are consistent with the definition of decision rule in rough set theory. To show the feasibility and effectiveness of our proposed decision rule, an experimental evaluation of rule acquisition is studied in a multi-decision data about cognitve real-world animals and the corresponding classification.

关键词： Cognitive computing Formal concept Multi-level cognitive Rule acquisition

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