Matches in SemOpenAlex for { <https://semopenalex.org/work/W2904269013> ?p ?o ?g. }
Showing items 1 to 98 of
98
with 100 items per page.
- W2904269013 abstract "Though RGB Cameras, Radar and LIDARs are popular sensors for intelligent vehicle systems, real-time joint inference on their sensory outputs remains challenging. Moreover, high-resolution LIDAR is expensive both in terms of cost and computation. This paper presents a deep learning-based pedestrian detection algorithm that takes both RGB image and lower-resolution LIDAR data and returns object detections in the image as 2-D bounding boxes, plus the distances of the detected objects. The proposed network is much less expensive but comparable in accuracy to previous deep networks that combine these sensors use image-like or voxel representations of LIDAR data to directly predict 3D positions and shapes. To train this network, a new dataset was created, containing register information from low-end camera a 16-layer LIDAR, and corresponding ground truth distance values generated by estimating the position of pedestrians from global navigation satellite system (GNSS) sensors and a fixed tower. The public release of this dataset is an additional contribution of this effort." @default.
- W2904269013 created "2018-12-22" @default.
- W2904269013 creator A5004886183 @default.
- W2904269013 creator A5007966510 @default.
- W2904269013 creator A5026161140 @default.
- W2904269013 creator A5058100924 @default.
- W2904269013 creator A5068100165 @default.
- W2904269013 creator A5069115743 @default.
- W2904269013 date "2018-11-01" @default.
- W2904269013 modified "2023-09-23" @default.
- W2904269013 title "Pedestrian Detection with Simplified Depth Prediction" @default.
- W2904269013 cites W1536680647 @default.
- W2904269013 cites W2031454541 @default.
- W2904269013 cites W2088049833 @default.
- W2904269013 cites W2102605133 @default.
- W2904269013 cites W2150066425 @default.
- W2904269013 cites W2151103935 @default.
- W2904269013 cites W2161969291 @default.
- W2904269013 cites W2169671170 @default.
- W2904269013 cites W2555618208 @default.
- W2904269013 cites W2562663242 @default.
- W2904269013 cites W2570343428 @default.
- W2904269013 cites W2594519801 @default.
- W2904269013 cites W2791003324 @default.
- W2904269013 cites W2793288154 @default.
- W2904269013 cites W2963037989 @default.
- W2904269013 cites W2963270286 @default.
- W2904269013 cites W2963351448 @default.
- W2904269013 cites W2963721253 @default.
- W2904269013 cites W2964184568 @default.
- W2904269013 doi "https://doi.org/10.1109/itsc.2018.8569987" @default.
- W2904269013 hasPublicationYear "2018" @default.
- W2904269013 type Work @default.
- W2904269013 sameAs 2904269013 @default.
- W2904269013 citedByCount "3" @default.
- W2904269013 countsByYear W29042690132019 @default.
- W2904269013 countsByYear W29042690132021 @default.
- W2904269013 countsByYear W29042690132023 @default.
- W2904269013 crossrefType "proceedings-article" @default.
- W2904269013 hasAuthorship W2904269013A5004886183 @default.
- W2904269013 hasAuthorship W2904269013A5007966510 @default.
- W2904269013 hasAuthorship W2904269013A5026161140 @default.
- W2904269013 hasAuthorship W2904269013A5058100924 @default.
- W2904269013 hasAuthorship W2904269013A5068100165 @default.
- W2904269013 hasAuthorship W2904269013A5069115743 @default.
- W2904269013 hasConcept C108583219 @default.
- W2904269013 hasConcept C14279187 @default.
- W2904269013 hasConcept C146849305 @default.
- W2904269013 hasConcept C154945302 @default.
- W2904269013 hasConcept C166957645 @default.
- W2904269013 hasConcept C205372480 @default.
- W2904269013 hasConcept C205649164 @default.
- W2904269013 hasConcept C2776151529 @default.
- W2904269013 hasConcept C2777113093 @default.
- W2904269013 hasConcept C2780156472 @default.
- W2904269013 hasConcept C31972630 @default.
- W2904269013 hasConcept C41008148 @default.
- W2904269013 hasConcept C51399673 @default.
- W2904269013 hasConcept C60229501 @default.
- W2904269013 hasConcept C62649853 @default.
- W2904269013 hasConcept C76155785 @default.
- W2904269013 hasConcept C82990744 @default.
- W2904269013 hasConcept C89600930 @default.
- W2904269013 hasConceptScore W2904269013C108583219 @default.
- W2904269013 hasConceptScore W2904269013C14279187 @default.
- W2904269013 hasConceptScore W2904269013C146849305 @default.
- W2904269013 hasConceptScore W2904269013C154945302 @default.
- W2904269013 hasConceptScore W2904269013C166957645 @default.
- W2904269013 hasConceptScore W2904269013C205372480 @default.
- W2904269013 hasConceptScore W2904269013C205649164 @default.
- W2904269013 hasConceptScore W2904269013C2776151529 @default.
- W2904269013 hasConceptScore W2904269013C2777113093 @default.
- W2904269013 hasConceptScore W2904269013C2780156472 @default.
- W2904269013 hasConceptScore W2904269013C31972630 @default.
- W2904269013 hasConceptScore W2904269013C41008148 @default.
- W2904269013 hasConceptScore W2904269013C51399673 @default.
- W2904269013 hasConceptScore W2904269013C60229501 @default.
- W2904269013 hasConceptScore W2904269013C62649853 @default.
- W2904269013 hasConceptScore W2904269013C76155785 @default.
- W2904269013 hasConceptScore W2904269013C82990744 @default.
- W2904269013 hasConceptScore W2904269013C89600930 @default.
- W2904269013 hasLocation W29042690131 @default.
- W2904269013 hasOpenAccess W2904269013 @default.
- W2904269013 hasPrimaryLocation W29042690131 @default.
- W2904269013 hasRelatedWork W2028766500 @default.
- W2904269013 hasRelatedWork W2128694549 @default.
- W2904269013 hasRelatedWork W2129431236 @default.
- W2904269013 hasRelatedWork W3004045746 @default.
- W2904269013 hasRelatedWork W3088831177 @default.
- W2904269013 hasRelatedWork W3162220967 @default.
- W2904269013 hasRelatedWork W4226383822 @default.
- W2904269013 hasRelatedWork W4312696271 @default.
- W2904269013 hasRelatedWork W4312857205 @default.
- W2904269013 hasRelatedWork W4324290760 @default.
- W2904269013 isParatext "false" @default.
- W2904269013 isRetracted "false" @default.
- W2904269013 magId "2904269013" @default.
- W2904269013 workType "article" @default.