Results 231 to 240 of about 6,770,857 (301)
In this work, low‐resolution infrared imaging is combined with a 28 nm FeFET IMC architecture to enable compact, energy‐efficient edge inference. MLC FeFET devices are experimentally characterized, and controlled multi‐level current accumulation is validated at crossbar array level.
Alptekin Vardar +9 more
wiley +1 more source
Q-AVOA-net: A multi-domain, quantum-inspired feature-selection and deep-fuzzy framework for interpretable white blood cell classification. [PDF]
Eslamifar O +2 more
europepmc +1 more source
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 +4 more
wiley +1 more source
Data-driven fuzzy information granulation for predicting freight volume trends. [PDF]
Gao Y, Wang X, Niu M, Li J, Cai L, Li R.
europepmc +1 more source
The amorphous tungsten (W) is found to be a promising non‐magnetic interlayer simultaneously driving the long‐range interlayer exchange coupling and the large spin Hall effect in a synthetic antiferromagnet (SyAF). Thanks to these characteristics, efficient spin‐orbit torque switching is achieved in the SyAF.
Xueyao Hou +9 more
wiley +1 more source
Theoretical foundations of soft topological granular structures for multi-criteria social network analysis. [PDF]
Oza A.
europepmc +1 more source
An ultrathin InxTiyO‐based optoelectronic synaptic device enables dual‐mode electrical and optical synaptic responses through charge‐trapping‐mediated conductance modulation. Multilevel conductance states further enable physical image encoding, converting visual information into spatial current distributions.
Chaerin Yu, Jung Wook Lim
wiley +1 more source
FuzzyFed-CNN: secure and explainable multimodal federated learning for early Alzheimer's diagnosis. [PDF]
Mohanraj S, Radhakrishnan S.
europepmc +1 more source
Advancing Energy Materials by In Situ Atomic Scale Methods
Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source

