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2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)最新文献

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A YOLO-Based Traffic Counting System 基于yolo的流量计数系统
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00027
Jia-Ping Lin, Min-Te Sun
{"title":"A YOLO-Based Traffic Counting System","authors":"Jia-Ping Lin, Min-Te Sun","doi":"10.1109/TAAI.2018.00027","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00027","url":null,"abstract":"Image recognition can be applied in many applications of Intelligent Transportation System. Through automated traffic flow counting, the traffic information can be presented effectively for a given area. After the existing image recognition model process the monitoring video, the coordinates of objects in each frame can be easily extracted. The extracted object coordinates are then filtered to obtain the required vehicle coordinates. To achieve the function of vehicle counting, it is necessary to identify the relationship of vehicles in different frames, i.e., whether or not they represent the same vehicle. Although the vehicle counting can be achieved by using the tracking algorithm, a short period of recognition failure may cause wrong tracking, which will lead to incorrect traffic counting. In this paper, we propose a system that utilizes the YOLO framework for traffic flow counting. The system architecture consists of three blocks, including the Detector that generates the bounding box of vehicles, the Buffer which stores coordinates of vehicles, and the Counter which is responsible for vehicle counting. The proposed system requires only to utilize simple distance calculations to achieve the purpose of vehicle counting. In addition, by adding checkpoints, the system is able to alleviate the consequence of false detection. The videos from different locations and angles are used to verify and analyze the correctness and overall efficiency of the proposed system, and the results indicate that our system achieves high counting accuracy under the environment with sufficient ambient light.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121616031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 57
Weighted Majority Voting with a Heterogeneous System in the Game of Shogi 将棋博弈中异构系统的加权多数投票
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00035
Shogo Takeuchi
{"title":"Weighted Majority Voting with a Heterogeneous System in the Game of Shogi","authors":"Shogo Takeuchi","doi":"10.1109/TAAI.2018.00035","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00035","url":null,"abstract":"In this paper, we propose a weighted voting method for a heterogeneous game system, which assigns the strength of engines and win probabilities of their positions to the weights for voting. Assigning the strength as the weight solves the problem of weaker engines entering the majority voting. The win probabilities are transformed from the evaluation values by a sigmoid function generated for each engine. Through the sigmoid functions, we can compare the win probabilities between the different engines and resolve the problem of optimistic voting in heterogeneous systems. Optimistic voting, which simply selects the highest-scoring move, may select a suboptimal random move when random players are involved in the game. Finally, we competed the proposed system and other voting systems against a single engine in shogi tournaments and compared the strengths of the systems in shogi. The experimental results confirmed the effectiveness of the proposed method.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116966057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Interpreting Neural-Network Players for Game 2048 解读Game 2048中的神经网络玩家
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00038
Kiminori Matsuzaki, Madoka Teramura
{"title":"Interpreting Neural-Network Players for Game 2048","authors":"Kiminori Matsuzaki, Madoka Teramura","doi":"10.1109/TAAI.2018.00038","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00038","url":null,"abstract":"Game 2048 is a stochastic single-player game and development of strong computer players for 2048 has been based on N-tuple networks trained by reinforcement learning. In our previous study, we developed computer players for game 2048 based on convolutional neural networks (CNNs), and showed by experiments that networks with three or more convolution layers performed much better than that with two convolution layers. In this study, we analyze the inner working of our CNNs (i.e. white box approach) to identify the reasons of the performance. Our analyses include visualization of filters in the first layers and backward trace of the networks for some specific game states. We report several findings about inner working of our CNNs for game 2048.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124582868","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Message from the TAAI 2018 Program Co-Chairs 2018年TAAI项目联合主席致辞
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/taai.2018.00006
Chao-Tung Yang, Chao Chen
{"title":"Message from the TAAI 2018 Program Co-Chairs","authors":"Chao-Tung Yang, Chao Chen","doi":"10.1109/taai.2018.00006","DOIUrl":"https://doi.org/10.1109/taai.2018.00006","url":null,"abstract":"The TAAI conference is an annual event that brings together researchers, engineers, and practitioners to present and exchange ideas, results, and experience in AI technologies and applications. This year, the conference received paper submissions from different countries. Every submission was assigned to at least two experts from the technical program committee to review. Due to the large amount of high-quality submissions, regular paper acceptance was very competitive. In addition, these proceedings feature high-quality papers. All of these papers provide novel ideas, new results, and state-of-the-art techniques in the field. We are honored to have several of the world’s leading experts in the field join us as distinguished keynote speakers. Altogether, we are proud to be able to present you a rich program that contains a variety of excellent researches.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131779009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Tongue Fissure Visualization with Deep Learning 舌裂可视化与深度学习
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00013
Wen-Hsien Chang, H. Chu, Hen-Hong Chang
{"title":"Tongue Fissure Visualization with Deep Learning","authors":"Wen-Hsien Chang, H. Chu, Hen-Hong Chang","doi":"10.1109/TAAI.2018.00013","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00013","url":null,"abstract":"Tongue diagnosis is a unique practice in traditional Chinese medicine(TCM), which can be used to infer the health condition of a person. However, different TCM doctors may give different interpretations on the same tongue. If an artificial intelligence model can be developed based on a large number of doctor-interpreted tongue images, a more objective judgment will be obtained. Deep learning in artificial intelligence has excellent performance in image recognition, and feature extraction can be done automatically by deep learning without image processing experts. This study attempts to develop a deep learning model through a large number of tongue images, especially for tongue fissures. We also visualize the fissure regions with Gradient-weighted Class Activation Mapping(Grad-cam). Therefore, the model not only try to detect tongue fissures but also localize tongue fissure regions.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131644344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
[Copyright notice] (版权)
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/taai.2018.00003
{"title":"[Copyright notice]","authors":"","doi":"10.1109/taai.2018.00003","DOIUrl":"https://doi.org/10.1109/taai.2018.00003","url":null,"abstract":"","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124307492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Application of Deep Reinforcement Learning in Werewolf Game Agents 深度强化学习在狼人博弈代理中的应用
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00016
Tianhe Wang, Tomoyuki Kaneko
{"title":"Application of Deep Reinforcement Learning in Werewolf Game Agents","authors":"Tianhe Wang, Tomoyuki Kaneko","doi":"10.1109/TAAI.2018.00016","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00016","url":null,"abstract":"Werewolf, also known as Mafia, is a kind of game with imperfect information. Werewolf game agents must cope with two kinds of problems, \"decision on who to trust or to kill\", and \"decision on information exchange\". In this paper, we focus on the first problem. We apply techniques in Deep Q Network in building werewolf agents. We also improve representation of states and actions based on existing agents trained by Q learning method. Our proposed agents were compared with existing agents trained by Q learning method and with existing agents submitted to the AIWolf Contest, the most famous werewolf game agents contest in Japan. For every role, we prepared four agents with proposed method and investigated average win ratio of four agents in our experiments. Experimental results showed that when agents learned and played with the same group of players, our proposed agents have better player performances than existing agents trained by Q learning method and a part of agents submitted to the AIWolf Contest. We obtained promising results by using reinforcement learning method to solve \"decision on who to trust or to kill\" problem without using heuristic methods.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125448800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Message from the TAAI 2018 General Co-Chairs 2018年TAAI联合主席致辞
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/taai.2018.00005
{"title":"Message from the TAAI 2018 General Co-Chairs","authors":"","doi":"10.1109/taai.2018.00005","DOIUrl":"https://doi.org/10.1109/taai.2018.00005","url":null,"abstract":"","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116782467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Learning of Evaluation Functions via Self-Play Enhanced by Checkmate Search 基于将军搜索的自我游戏评价函数学习
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00036
T. Nakayashiki, Tomoyuki Kaneko
{"title":"Learning of Evaluation Functions via Self-Play Enhanced by Checkmate Search","authors":"T. Nakayashiki, Tomoyuki Kaneko","doi":"10.1109/TAAI.2018.00036","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00036","url":null,"abstract":"As shown in AlphaGo, AlphaGo Zero, and AlphaZero, reinforcement learning is effective in learning of evaluation functions (or value networks) in Go, Chess and Shogi. In their training, two procedures are repeated in parallel; self-play with a current evaluation function and improvement of the evaluation function by using game records yielded by recent self-play. Although AlphaGo, AlphaGo Zero, and AlphaZero have achieved super human performance, the method requires enormous computation resources. To alleviate the problem, this paper proposes to incorporate a checkmate solver in self-play. We show that this small enhancement dramatically improves the efficiency of our experiments in Minishogi, via the quality of game records in self-play. It should be noted that our method is still free from human knowledge about a target domain, though the implementation of checkmate solvers is domain dependent.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123165547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Rating Matrix Pre-Padding for Video Recommendation 视频推荐的评级矩阵预填充
2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI) Pub Date : 2018-11-01 DOI: 10.1109/TAAI.2018.00044
Yang Liu, Guijuan Zhang, Xiaoning Jin, Yaozong Jia
{"title":"Rating Matrix Pre-Padding for Video Recommendation","authors":"Yang Liu, Guijuan Zhang, Xiaoning Jin, Yaozong Jia","doi":"10.1109/TAAI.2018.00044","DOIUrl":"https://doi.org/10.1109/TAAI.2018.00044","url":null,"abstract":"The personalized video recommendation system provides users with great convenience while surfing in the video websites. Among many algorithms adopted by recommendation system, the collaborative filtering algorithm is the most widely used and has achieved great success in practical applications, however, the recommended performance suffers from the problem of data sparsity severely. We propose a model that adopts Doc2Vec to deal with video's text information and integrates genre information into rating matrix pre-padding to reduce the sparsity of ratings. The experimental results show that pre-padding ratings is of high quality and the algorithms based on collaborative filtering achieve better performance on the padded datasets.","PeriodicalId":211734,"journal":{"name":"2018 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116125211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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