Results 71 to 80 of about 535,457 (208)

Rendering visual events as sounds: Spatial attention capture by auditory augmented reality.

PLoS ONE, 2017
Many salient visual events tend to coincide with auditory events, such as seeing and hearing a car pass by. Information from the visual and auditory senses can be used to create a stable percept of the stimulus. Having access to related coincident visual
Scott A Stone, Matthew S Tata
doaj   +1 more source

Covert Optical Fingerprints Within Overt Structural Colors via Cascaded Cavity Resonances

Advanced Science, EarlyView.
Cascaded photonic–plasmonic cavities combine vivid structural colors with hidden stochastic optical fingerprints in a single monolithic platform. Layered cavities control the overt appearance, while disordered nanogap resonances generate covert scattering with limited mutual influence.
Gyurin Kim, Jiyeong Ma, Juhwan Kim, JuHyeong Lee, Heungchan Kwon, Young Min Song, Hyeon‐Ho Jeong   +6 more
wiley   +1 more source

4D event imaging with a single neuromorphic camera

Advanced Photonics Nexus
Neuromorphic cameras, or dynamic vision sensors, are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level. Recently, they garnered increasing interest due to their extremely high temporal resolution, wide dynamic range, low power consumption, and high pixel bandwidth.
Raviv Ilani, Adrian Stern
openaire   +1 more source

RN‐Net: Reservoir Nodes‐Enabled Neuromorphic Vision Sensing Network

Advanced Intelligent Systems
Neuromorphic computing systems promise high energy efficiency and low latency. In particular, when integrated with neuromorphic sensors, they can be used to produce intelligent systems for a broad range of applications.
Sangmnin Yoo, Eric Yeu‐Jer Lee, Ziyu Wang, Xinxin Wang, Wei D. Lu   +4 more
doaj   +1 more source

Serendipitous Offline Learning in a Neuromorphic Robot

Frontiers in Neurorobotics, 2016
We demonstrate a hybrid neuromorphic learning paradigm that learns complex sensorimotor mappings based on a small set of hard-coded reflex behaviours. A mobile robot is first controlled by a basic set of reflexive hand-designed behaviours.
Terrence C Stewart, Andrew eMundy, Ashley eKleinhans, Jorg eConradt   +3 more
doaj   +1 more source

Polarity‐Controlled Coexistence of Electrochemical Metallization and Valence Change Mechanisms in a Unified Metal Halide Perovskite Memristor

Advanced Science, EarlyView.
Electrochemical metallization and valence change mechanisms are shown to coexist within a single metal halide perovskite memristor, selectively activated by simply reversing the electroforming voltage polarity. Ag‐driven switching delivers low operating voltages and high endurance, while intrinsic ion migration yields superior retention and resistance ...
Ismael Fernandez‐Guillen, Omar E. Solis, Pablo F. Betancur, Rafael Abargues, Pablo P. Boix   +4 more
wiley   +1 more source

Metasurface‐Based Multidimensional Light‐Field Manipulation: From Technologies to Applications

Advanced Science, EarlyView.
Multidimensional metasurfaces enable versatile manipulation of multiple optical degrees of freedom, including phase, amplitude, polarization, wavelength, and orbital angular momentum. This review summarizes their fundamental mechanisms, emerging strategies for multidimensional light‐field control, and key applications in optical computing, imaging ...
Heliang Yin, Shuo Sun, Jiahao Zhang, Jianuo Hu, Yubin Qiao, Liang Chen, Jin Li   +6 more
wiley   +1 more source

N-Omniglot: a Large-scale Neuromorphic Dataset for Spatio-temporal Sparse Few-shot Learning

, 2021
N-Omniglot is a large neuromorphic few-shot learning dataset. It reconstructs strokes of Omniglot as videos and uses Davis346 to capture the writing of the characters.
Yiting Dong (11809626), Dongcheng Zhao (11809661), Yi Zeng (11809698), Yang Li (11386029)   +3 more
core   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

Advanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez, Raúl Parada, Jordi Casas‐Roma, Laia Subirats   +3 more
wiley   +1 more source