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You searched for subject:(voxel map). Showing records 1 – 3 of 3 total matches.

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1. Heikkilä, Filip. Autonomous Mapping of Unknown Environments Using a UAV .

Degree: Chalmers tekniska högskola / Institutionen för matematiska vetenskaper, 2020, Chalmers University of Technology

Automatic object search in a bounded area can be accomplished using cameracarrying autonomous aerial robots. The system requires several functionalities to solve the task in a safe and efficient way, including finding a navigation and exploration strategy, creating a representation of the surrounding environment and detecting objects visually. Here we create a modular framework and provide solutions to the different subproblems in a simulated environment. The navigation and exploration subproblems are tackled using deep reinforcement learning (DRL). Object and obstacle detection is approached using methods based on the scale-invariant feature transform and the pinhole camera model. Information gathered by the system is used to build a 3D voxel map. We further show that the object detection system is capable of detecting certain target objects with high recall. The DRL approach is able to achieve navigation that avoids collisions to a high degree, but the performance of the exploration policy is suboptimal. Due to the modular character of the solution further improvements of each subsystems can easily be developed independently.

Subjects/Keywords: Deep reinforcement learning; autonomous exploration and navigation; feature extraction; object detection; voxel map; UAV; modular framework.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Heikkilä, F. (2020). Autonomous Mapping of Unknown Environments Using a UAV . (Thesis). Chalmers University of Technology. Retrieved from http://hdl.handle.net/20.500.12380/300894

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Heikkilä, Filip. “Autonomous Mapping of Unknown Environments Using a UAV .” 2020. Thesis, Chalmers University of Technology. Accessed November 27, 2020. http://hdl.handle.net/20.500.12380/300894.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Heikkilä, Filip. “Autonomous Mapping of Unknown Environments Using a UAV .” 2020. Web. 27 Nov 2020.

Vancouver:

Heikkilä F. Autonomous Mapping of Unknown Environments Using a UAV . [Internet] [Thesis]. Chalmers University of Technology; 2020. [cited 2020 Nov 27]. Available from: http://hdl.handle.net/20.500.12380/300894.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Heikkilä F. Autonomous Mapping of Unknown Environments Using a UAV . [Thesis]. Chalmers University of Technology; 2020. Available from: http://hdl.handle.net/20.500.12380/300894

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Kyoto University / 京都大学

2. Inano, Rika. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測.

Degree: 博士(医学), 2016, Kyoto University / 京都大学

新制・課程博士

甲第19616号

医博第4123号

Subjects/Keywords: glioma grading; diffusion tendor imaging; voxel-based clustering; self-organizing map; K-means; support vector machine

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Inano, R. (2016). Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測. (Thesis). Kyoto University / 京都大学. Retrieved from http://hdl.handle.net/2433/215442 ; http://dx.doi.org/10.14989/doctor.k19616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Inano, Rika. “Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測.” 2016. Thesis, Kyoto University / 京都大学. Accessed November 27, 2020. http://hdl.handle.net/2433/215442 ; http://dx.doi.org/10.14989/doctor.k19616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Inano, Rika. “Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測.” 2016. Web. 27 Nov 2020.

Vancouver:

Inano R. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測. [Internet] [Thesis]. Kyoto University / 京都大学; 2016. [cited 2020 Nov 27]. Available from: http://hdl.handle.net/2433/215442 ; http://dx.doi.org/10.14989/doctor.k19616.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Inano R. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading : 拡散テンソル画像の複数パラメータを用いた神経膠腫の悪性度予測. [Thesis]. Kyoto University / 京都大学; 2016. Available from: http://hdl.handle.net/2433/215442 ; http://dx.doi.org/10.14989/doctor.k19616

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Inano, Rika. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading .

Degree: 2016, Kyoto University

Subjects/Keywords: glioma grading; diffusion tendor imaging; voxel-based clustering; self-organizing map; K-means; support vector machine

Page 1 Page 2 Page 3

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Inano, R. (2016). Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading . (Thesis). Kyoto University. Retrieved from http://hdl.handle.net/2433/215442

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Inano, Rika. “Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading .” 2016. Thesis, Kyoto University. Accessed November 27, 2020. http://hdl.handle.net/2433/215442.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Inano, Rika. “Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading .” 2016. Web. 27 Nov 2020.

Vancouver:

Inano R. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading . [Internet] [Thesis]. Kyoto University; 2016. [cited 2020 Nov 27]. Available from: http://hdl.handle.net/2433/215442.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Inano R. Voxel-based clustered imaging by multiparameter diffusion tensor images for glioma grading . [Thesis]. Kyoto University; 2016. Available from: http://hdl.handle.net/2433/215442

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.