Results 131 to 140 of about 22,182 (296)
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Second-Quantization Formalism for Geminals
A method of constructing second-quantization formalism on a set of orthonormal geminals (two-particle antisymmetric functions) is described. Instead of using an initial set of creation and annihilation operators with nontrivial commutation rules, the ...
Kvasnicka, Vladimir, Vladimir Kvasnicka
core
Intrinsic stationarity for vector quantization: Foundation of dual quantization
International audienceWe develop a new approach to vector quantization, which guarantees an intrinsic stationarity property that also holds, in contrast to regular quantization, for non-optimal quantization grids.
Wilbertz, Benedikt, Pagès, Gilles
core +1 more source
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo +5 more
wiley +1 more source
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto +3 more
wiley +1 more source
Speed up integer-arithmetic-only inference via bit-shifting
Quantization is a widely adopted technique in model deployment as it offers a favorable trade-off between computational overhead and performance loss.
Mingjun Song +5 more
doaj +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source
A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song +21 more
wiley +1 more source
Detectores de partículas sobre variedades no Minkowskianas
The concepts of particle and vacuum are discussed using differents detector's models and are compared with those that arise from the second quantization method on a non-Minkowskian manifold.
J. M. Tejeiro
doaj

