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Near-infrared germanium PIN-photodiodes with >1A/W responsivity.
Light Sci Appl
January 2025
Aalto University, Department of Electronics and Nanoengineering, Espoo, Finland.
Even though efficient near-infrared (NIR) detection is critical for numerous applications, state-of-the-art NIR detectors either suffer from limited capability of detecting incoming photons, i.e., have poor spectral responsivity, or are made of expensive group III-V non-CMOS compatible materials.
View Article and Find Full Text PDFAutomatic brake Driver Assistance System based on deep learning and fuzzy logic.
PLoS One
December 2024
Tecnológico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Zapopan, Jalisco, México.
Advanced Driver Assistance Systems (ADAS) aim to automate transportation fully. A key part of this automation includes tasks such as traffic light detection and automatic braking. While indoor experiments are prevalent due to computational demands and safety concerns, there is a pressing need for research and development of new features to achieve complete automation, addressing real-world implementation challenges by testing them in outdoor environments.
View Article and Find Full Text PDF- a large-scale dataset of 3D medical shapes for computer vision.
Biomed Tech (Berl)
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Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen (AöR), Essen, Germany.
Objectives: The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models).
View Article and Find Full Text PDFA reinforcement learning based memetic algorithm for energy-efficient distributed two-stage flexible job shop scheduling problem.
Sci Rep
December 2024
Information Construction and Management Center, Nanyang Institute of Technology, Nanyang, 473004, Henan, China.
Given the increasingly severe environmental challenges, distributed green manufacturing has garnered significant academic and industrial interest. This paper addresses the distributed two-stage flexible job shop scheduling problem (DTFJSP) under time-of-use (TOU) electricity pricing, with the objective of minimizing both makespan and total energy consumption costs (TEC). To tackle the problem, a hybrid memetic algorithm (HMA) is proposed.
View Article and Find Full Text PDFPath planning and engineering problems of 3D UAV based on adaptive coati optimization algorithm.
Sci Rep
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Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, 550025, Guizhou, China.
In response to the challenges faced by the Coati Optimization Algorithm (COA), including imbalance between exploration and exploitation, slow convergence speed, susceptibility to local optima, and low convergence accuracy, this paper introduces an enhanced variant termed the Adaptive Coati Optimization Algorithm (ACOA). ACOA achieves a balanced exploration-exploitation trade-off through refined exploration strategies and developmental methodologies. It integrates chaos mapping to enhance randomness and global search capabilities and incorporates a dynamic antagonistic learning approach employing random protons to mitigate premature convergence, thereby enhancing algorithmic robustness.
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