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Radatron: Accurate Detection Using Multi-resolution Cascaded MIMO Radar
Related publications (39)
Predicting the long-term collective behaviour of fish pairs with deep learning
Francesco Mondada, Alexandre Massoud Alahi, Vaios Papaspyros
Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...
2024Rigidity-Aware Detection for 6D Object Pose Estimation
Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song
Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...
Los Alamitos2023AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES
Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...
New York2023Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations
Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...
EPFL2023Text Representation Learning for Low Cost Natural Language Understanding
Jan Frederik Jonas Florian Mai
Natural language processing and other artificial intelligence fields have witnessed impressive progress over the past decade. Although some of this progress is due to algorithmic advances in deep learning, the majority has arguably been enabled by scaling ...
EPFL2023Reshaping Perception for Autonomous Driving with Semantic Keypoints
The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...
EPFL2022Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models
Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...
EPFL2022Automation of the diagnosis process in the railway system : Detection of defects in concrete sleepers using vision-based machine learning models
inspectors that walk over the track and check the defects on the rail surface, fasteners and sleepers. In the case of concrete sleepers, rail inspectors classify defects according to their size and occurrence over 20 sleepers. The manual inspection is erro ...
2021Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks
Sabine Süsstrunk, Majed El Helou, Deblina Bhattacharjee, Xiaoyu Lin
Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...
2021The role of convolutional neural networks in scanning probe microscopy: a review
Progress in computing capabilities has enhanced science in many ways. In recent years, various branches of machine learning have been the key facilitators in forging new paths, ranging from categorizing big data to instrumental control, from materials desi ...
BEILSTEIN-INSTITUT2021