Extremely popular and commonly adopted microblogging service is not only a new form of communication, but also seen as a place for "fueling" viral marketing. Due to essential openness and growing ubiquity, m...
详细信息
Precision management of agricultural systems, aiming at optimizing profitability, productivity and sustainability, comprises a set of technologies including sensors, information systems, and informed management, etc. ...
详细信息
Social multimedia content had an unprecedented increasing trend in recent years, and receiving a number of research attentions. Images, an exceedingly expressive form of social multimedia, can be widely seen in news r...
详细信息
Social multimedia content had an unprecedented increasing trend in recent years, and receiving a number of research attentions. Images, an exceedingly expressive form of social multimedia, can be widely seen in news report for social emergency. Among the vast number of images for social emergency are many repurposed images, that is, variants not interpreted as what the original images express. Such repurposed images appear in many online pages and may mislead the public. This make it being an interesting and challenging task to identify whether an image is repurposed. We propose a novel framework, called SOFC, to identify the repurposed images. A SIFT-based identical parts finding algorithm is used to find and align all potential identical blocks in the repurposed images and the original images. We then compute the similarity of the potential identical blocks by implementing an object-based likelihood measuring algorithm, to determine whether these blocks are identical in the two images. Finally, the effectiveness of the proposed identification method is validated by experiments on a image set of real social emergency.
In this paper, we propose a novel method based on the combination of Named Entity Recognition and Entity Rank algorithm for detecting key entities with significant influence and importance from huge sentiment data col...
详细信息
In this paper, we propose a novel method based on the combination of Named Entity Recognition and Entity Rank algorithm for detecting key entities with significant influence and importance from huge sentiment data collected from Internet. Firstly, we extract entities from the target news websites and forums using a rule-based and CRF combined method. Secondly, we use the Entity Rank algorithm to calculate the hotness of entities extracted from the news and forums data. Finally, we validate the rationality of our algorithm by comparing our hot entities and current affairs. We believe this work will shed new lights on the online public sentiment supervision.
A promising P2P application, P2P-TV, has attracted hundreds of thousands of Chinese viewers. These viewers who are located in different regions represent groups with distinct cultures. However, little existing researc...
详细信息
A promising P2P application, P2P-TV, has attracted hundreds of thousands of Chinese viewers. These viewers who are located in different regions represent groups with distinct cultures. However, little existing research has provided sufficient insights into the societal impact of P2P-TV systems, from the viewpoint of geographic distribution of viewers. In this paper, we analyze geographic distribution of viewers of three most popular P2P-TV systems simultaneously, PPLive, PPStream and UUSee. With more than 20 GB worth of log data from three different P2P-TV systems, we have completed a thorough investigation of geographic distribution of viewers. We also seek to explore the potential correlation between viewer population density and economic development level and find that there is indeed a highly negative correlation between them.
The effect evaluation of chemical emergency response plans before implementation is an important research topic. Most researchers focus on the evaluation of chemical objective process and ignore the impact of human be...
详细信息
Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adver...
详细信息
Recently, generative adversarial networks(GANs)have become a research focus of artificial intelligence. Inspired by two-player zero-sum game, GANs comprise a generator and a discriminator, both trained under the adversarial learning *** goal of GANs is to estimate the potential distribution of real data samples and generate new samples from that *** their initiation, GANs have been widely studied due to their enormous prospect for applications, including image and vision computing, speech and language processing, etc. In this review paper, we summarize the state of the art of GANs and look into the future. Firstly, we survey GANs' proposal background,theoretic and implementation models, and application ***, we discuss GANs' advantages and disadvantages, and their development trends. In particular, we investigate the relation between GANs and parallel intelligence,with the conclusion that GANs have a great potential in parallelsystems research in terms of virtual-real interaction and integration. Clearly, GANs can provide substantial algorithmic support for parallel intelligence.
In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data. However, collecting and annotating images from the real world is too demanding in term...
详细信息
In the area of computer vision, deep learning has produced a variety of state-of-the-art models that rely on massive labeled data. However, collecting and annotating images from the real world is too demanding in terms of labor and money investments, and is usually inflexible to build datasets with specific characteristics, such as small area of objects and high occlusion level. Under the framework of parallel Vision, this paper presents a purposeful way to design artificial scenes and automatically generate virtual images with precise annotations.A virtual dataset named parallel Eye is built, which can be used for several computer vision tasks. Then, by training the DPM(Deformable parts model) and Faster R-CNN detectors, we prove that the performance of models can be significantly improved by combining parallel Eye with publicly available real-world datasets during the training phase. In addition, we investigate the potential of testing the trained models from a specific aspect using intentionally designed virtual datasets, in order to discover the flaws of trained models. From the experimental results, we conclude that our virtual dataset is viable to train and test the object detectors.
Cryptocurrency and blockchain technologies have developed in parallel in recent years, with technological breakthroughs in currency issuance, payment methods, and currency storage. However, the existing cryptocurrenci...
详细信息
The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, parallel Driving, a clo...
详细信息
The emerging development of connected and automated vehicles imposes a significant challenge on current vehicle control and transportation systems. This paper proposes a novel unified approach, parallel Driving, a cloud-based cyberphysical-social systems(CPSS) framework aiming at synergizing connected automated driving. This study first introduces the CPSS and ACP-based intelligent machine systems. Then the parallel driving is proposed in the cyber-physical-social space,considering interactions among vehicles, human drivers, and information. Within the framework, parallel testing, parallel learning and parallel reinforcement learning are developed and concisely reviewed. Development on intelligent horizon(iHorizon)and its applications are also presented towards parallel *** proposed parallel driving offers an ample solution for achieving a smooth, safe and efficient cooperation among connected automated vehicles with different levels of automation in future road transportation systems.
暂无评论