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Publication search results
found 133 matches
- 2023
- Tim Brophy, Brian M. Deegan, Javier Salado, Ángel Tena, Patrick Denny, Martin Glavin, Enda Ward, Jonathan Horgan, Edward Jones:
The design and validation of a rain model for a simulated automotive environment. Autonomous Vehicles and Machines 2023: 1-6 - Brian M. Deegan, Dara Molloy, Jordan Cahill, Jonathan Horgan, Enda Ward, Edward Jones, Martin Glavin:
The influence of image capture and processing on MTF for end of line test and validation. Autonomous Vehicles and Machines 2023: 126-1 - Shyam Jagannathan, Vijay Pothukuchi, Jesse Villarreal, Kumar Desappan, Manu Mathew, Rahul Ravikumar, Aniket Limaye, Mihir Mody, Pramod Swami, Piyali Goswami, Carlos Rodriguez, Emmanuel Madrigal, Marco Herrera:
OpTIFlow - An optimized end-to-end dataflow for accelerating deep learning workloads on heterogeneous SoCs. Autonomous Vehicles and Machines 2023: 113-1 - Jackson Knappen:
Comprehensive stray light (flare) testing: Lessons learned. Autonomous Vehicles and Machines 2023: 1-7 - Shimiao Li, Yang Song, Ruijiang Luo, Zhongyang Huang, Chengming Liu:
tRANSAC: Dynamic feature accumulation across time for stable online RANSAC model estimation in automotive applications. Autonomous Vehicles and Machines 2023: 1-6 - Hao Lin, Brian M. Deegan, Jonathan Horgan, Enda Ward, Patrick Denny, Ciarán Eising, Martin Glavin, Edward Jones:
Simulating motion blur and exposure time and evaluating its effect on image quality. Autonomous Vehicles and Machines 2023: 117-1 - Zhenyi Liu, Devesh Shah, Alireza Rahimpour, Devesh Upadhyay, Joyce E. Farrell, Brian A. Wandell:
Using simulation to quantify the performance of automotive perception systems. Autonomous Vehicles and Machines 2023: 1-8 - Chen-Chou Lo, Patrick Vandewalle:
How much depth information can radar contribute to a depth estimation model? Autonomous Vehicles and Machines 2023: 1-7 - Mihir Mody, Kumar Desappan, Pramod Swami, David Smith, Shyam Jagannathan, Kevin Lavery, Gregory Shultz, Jason Jones:
Orchestration of co-operative and adaptive multi-core deep learning engines. Autonomous Vehicles and Machines 2023: 1-5 - Patrick Müller, Alexander Braun:
MTF as a performance indicator for AI algorithms? Autonomous Vehicles and Machines 2023: 1-7 - Dominik Schörkhuber, Roman Popp, Oleksandr Chistov, Fabian Windbacher, Michael Hödlmoser, Margrit Gelautz:
Design of an automotive platform for computer vision research. Autonomous Vehicles and Machines 2023: 1-6 - Shihao Shen, Louis Kerofsky, Senthil Kumar Yogamani:
Optical flow for autonomous driving: Applications, challenges and improvements. Autonomous Vehicles and Machines 2023: 1-8 - Praneet Singh, Edward J. Delp, Amy R. Reibman:
End-to-end evaluation of practical video analytics systems for face detection and recognition. Autonomous Vehicles and Machines 2023: 1-6 - Autonomous Vehicles and Machines 2023, San Francisco, CA, USA, January 15-19, 2023. Society for Imaging Science and Technology 2023 [contents]
- 2022
- Ganesh Babu, Ramchandra Cheke, Ganesh Sistu, Senthil Kumar Yogamani:
Multi-lane modelling using convolutional neural networks and conditional random fields. Autonomous Vehicles and Machines 2022: 1-6 - Peter van Beek, Chyuan-Tyng Wu, Avi Kalderon:
Efficient high-dynamic-range depth map processing with reduced precision neural net accelerator. Autonomous Vehicles and Machines 2022: 1-5 - Mattis Brummel, Patrick Müller, Alexander Braun:
Spatial precision and recall indices to assess the performance of instance segmentation algorithms. Autonomous Vehicles and Machines 2022: 1-6 - Ramchandra Cheke, Ganesh Sistu, Ciarán Eising, Pepijn van de Ven, Varun Ravi Kumar, Senthil Kumar Yogamani:
FisheyePixPro: Self-supervised pretraining using Fisheye images for semantic segmentation. Autonomous Vehicles and Machines 2022: 1-6 - Brian M. Deegan:
A review of IEEE P2020 flicker metrics. Autonomous Vehicles and Machines 2022: 1-6 - Kumar Desappan, Anand Pathak, Pramod Swami, Mihir Mody, Yuan Zhao, Paula Carrillo, Praveen Eppa, Jianzhong Xu:
Open source deep learning inference libraries for autonomous driving systems. Autonomous Vehicles and Machines 2022: 1-5 - Marius Dupuis:
Paving the way for certified performance: Quality assessment and rating of simulation solutions for ADAS and autonomous driving. Autonomous Vehicles and Machines 2022: 1-6 - Eiichi Funatsu, Steve Wang, Jken Vui Kok, Lou Lu, Fred Cheng, Mario Heid:
Non-RGB color filter options and traffic signal detection capabilities. Autonomous Vehicles and Machines 2022: 1-6 - Paola Iacomussi, Alessandro Schiavi:
Toward metrological trustworthiness for automated and connected mobility. Autonomous Vehicles and Machines 2022: 1-5 - Jisan Lee, Kyunghyun Son, Chang-Bum Lee, Inoh Hwang, Bongyong Jang, Eun Kyung Lee, Dongshik Shim, Hyunil Byun, Changgyun Shin, Tatsuhiro Otsuka, Yongchul Cho, Kyoungho Ha, Hyuck Choo:
Real-time LIDAR imaging by solid-state single chip beam scanner. Autonomous Vehicles and Machines 2022: 1-4 - Mayank Mangla, Mihir Mody, Kedar Chitnis, Piyali Goswami, Tarkesh Pande, Shashank Dabral, Shyam Jagannathan, Stefan Haas, Gang Hua, Hrushikesh Garud, Kumar Desappan, Prithvi Shankar, Niraj Nandan:
Efficient in-cabin monitoring solution using TI TDA2PxSOCs. Autonomous Vehicles and Machines 2022: 1-5 - Orit Skorka, Paul Romanczyk:
A review of IEEE P2020 noise metrics. Autonomous Vehicles and Machines 2022: 1-6 - Ibrahim Sobh, Ahmed Hamed, Varun Ravi Kumar, Senthil Kumar Yogamani:
Adversarial Attacks on Multi-task Visual Perception for Autonomous Driving. Autonomous Vehicles and Machines 2022: 1-9 - Korbinian Weikl, Damien Schroeder, Walter Stechele:
Potentials of combined visible light and near infrared imaging for driving automation. Autonomous Vehicles and Machines 2022: 1-5 - Luis Constantin Wohlers, Patrick Müller, Alexander Braun:
Original image noise reconstruction for spatially-varying filtered driving scenes. Autonomous Vehicles and Machines 2022: 1-7 - Autonomous Vehicles and Machines 2022 Conference Overview and Papers Program. Autonomous Vehicles and Machines 2022
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