Zobrazeno 1 - 10
of 1 367
pro vyhledávání: '"Hauswirth P"'
Recently, deep learning has experienced rapid expansion, contributing significantly to the progress of supervised learning methodologies. However, acquiring labeled data in real-world settings can be costly, labor-intensive, and sometimes scarce. Thi
Externí odkaz:
http://arxiv.org/abs/2411.19143
Autor:
Shuai, Jiangtao, Baerveldt, Martin, Nguyen-Duc, Manh, Le-Tuan, Anh, Hauswirth, Manfred, Le-Phuoc, Danh
This paper presents a preliminary study of an efficient object tracking approach, comparing the performance of two different 3D point cloud sensory sources: LiDAR and stereo cameras, which have significant price differences. In this preliminary work,
Externí odkaz:
http://arxiv.org/abs/2411.18476
In this paper, we present an experimental comparison of various graph-based approximate nearest neighbor (ANN) search algorithms deployed on edge devices for real-time nearest neighbor search applications, such as smart city infrastructure and autono
Externí odkaz:
http://arxiv.org/abs/2411.14006
Search and rescue operations require mobile robots to navigate unstructured indoor and outdoor environments. In particular, actively stabilized multirotor drones need precise movement data to balance and avoid obstacles. Combining radial velocities f
Externí odkaz:
http://arxiv.org/abs/2408.05764
Autor:
Seidel, Raphael, Bock, Sebastian, Zander, René, Petrič, Matic, Steinmann, Niklas, Tcholtchev, Nikolay, Hauswirth, Manfred
While significant progress has been made on the hardware side of quantum computing, support for high-level quantum programming abstractions remains underdeveloped compared to classical programming languages. In this article, we introduce Qrisp, a fra
Externí odkaz:
http://arxiv.org/abs/2406.14792
Unsupervised Domain Adaptation (UDA) has shown significant advancements in object detection under well-lit conditions; however, its performance degrades notably in low-visibility scenarios, especially at night, posing challenges not only for its adap
Externí odkaz:
http://arxiv.org/abs/2404.01988
Autor:
Seidel, Raphael, Zander, René, Petrič, Matic, Steinmann, Niklas, Liu, David Q., Tcholtchev, Nikolay, Hauswirth, Manfred
The quantum backtracking algorithm proposed by Ashley Montanaro raised considerable interest, as it provides a quantum speed-up for a large class of classical optimization algorithms. It does not suffer from Barren-Plateaus and transfers well into th
Externí odkaz:
http://arxiv.org/abs/2402.10060
Autor:
Yuan, Jicheng, Le-Tuan, Anh, Nguyen-Duc, Manh, Tran, Trung-Kien, Hauswirth, Manfred, Le-Phuoc, Danh
The availability of vast amounts of visual data with heterogeneous features is a key factor for developing, testing, and benchmarking of new computer vision (CV) algorithms and architectures. Most visual datasets are created and curated for specific
Externí odkaz:
http://arxiv.org/abs/2309.13610
Uncomputation is an essential part of reversible computing and plays a vital role in quantum computing. Using this technique, memory resources can be safely deallocated without performing a nonreversible deletion process. For the case of quantum comp
Externí odkaz:
http://arxiv.org/abs/2307.11417
Publikováno v:
Phys. Rev. Research 6, 013330 (2024)
Quantum information processing architectures typically only allow for nearest-neighbour entanglement creation. In many cases, this prevents the direct generation of GHZ states, which are commonly used for many communication and computation tasks. Her
Externí odkaz:
http://arxiv.org/abs/2211.16758