Nagoya , Japan
Submission Deadline: Monday 15 Feb 2021
Conference Dates: Jul 11, 2021 - Jul 17, 2021
IEEE Intelligent Vehicles Symposium primarily tackles Artificial intelligence, Computer vision, Object detection, Simulation and Vehicle dynamics. The work on Artificial intelligence tackled in IEEE Intelligent Vehicles Symposium brings together disciplines like Machine learning and Pattern recognition. Computer vision research featured in the event incorporates concerns from various other topics such as Lidar and Advanced driver assistance systems.
In the event, Pedestrian detection and Contextual image classification are investigated in conjunction with one another to address concerns in Object detection research. IEEE Intelligent Vehicles Symposium focuses on Simulation as well as the interrelated topic of Real-time computing. In the conference, researchers investigate the Vehicle dynamics study as part of research in the field of Control theory.
The study of Control engineering and how it intertwines with concepts under Control (management) were explored in the presented Control theory research. Studies on Feature extraction discussed in it link to the field of Feature (computer vision). The Trajectory study tackled is a key component of adjacent topics in the area of Motion planning.
Artificial intelligence, Computer vision, Object detection, Advanced driver assistance systems and Simulation are the main subjects of interest in the published papers. The conference articles explore topics in Artificial intelligence which can be helpful for research in disciplines like Machine learning and Pattern recognition. While Computer vision is the key highlight in the conference publications, thet also covered some subjects on Kalman filter and Sensor fusion.
The foci of IEEE Intelligent Vehicles Symposium are Artificial intelligence, Motion planning, Aerospace engineering, Field (physics) and Binary neural network. It centers on topics in Artificial intelligence, with a focus on Pruning (decision trees). Motion planning research presented in the conference encompasses a variety of subjects, including Robotics, Theoretical computer science, Reachability, Set (abstract data type) and Risk analysis (engineering).
While work presented in the conference provided substantial information on Binary neural network, it also covered topics in Traffic sign detection and Pattern recognition.
A key indicator for each conference is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing at IEEE Intelligent Vehicles Symposium (based on the number of publications) are:
The overall trend for top authors publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing at IEEE Intelligent Vehicles Symposium (based on the number of publications) are:
The overall trend for top affiliations publishing at this conference is outlined below. The chart shows the number of publications at each edition of the conference for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions at the conference edition to all articles published within that conference. The best research institutions were selected based on the largest number of articles published during all editions of the conference.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 11.11% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 75.00% were posted by at least one author from the top 10 institutions publishing at the conference. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 25.00% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of conferences they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same conference from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the conference in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing at a conference. The index includes the authors publishing at the last edition of a conference, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
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Deadline: Saturday 15 Oct 2022
IV21 32nd IEEE Intelligent Vehicles Symposium
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