Tom's Hardware on MSN

SK hynix and TetraMem collaborate on experimental chip to bolster edge AI energy efficiency

SK hynix, TetraMem, and the University of Southern California built a memristor-based in-memory computing system-on-chip for ...
Interesting Engineering on MSN

New in-memory computing chip promises faster processing with lower energy use

Artificial intelligence chip developers SK hynix and TetraMem have demonstrated a new memory-centric processor ...

A New Way To See Life’s Hidden Chemistry: $10 Spectrometer Could Turn Wearables Into Personal Health Labs

Researchers have developed a compact, low-cost convolutional spectrometer that delivers lab-grade precision for applications ...

WiMi Develops Quantum Convolutional Neural Network Model for Classical Data Classification

WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WIMI" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, has completed systematic benchmark testing on fully ...
eeworldonline

How to use convolution to implement filters: part 2

A moving-average filter can address white noise in the time domain but performs poorly in the frequency domain. In part 1 of this series, we defined convolution, denoted by the * symbol, and looked at ...
Frontiers

High-efficiency sparse convolution operator for event-based cameras

Event-based cameras are bio-inspired vision sensors that mimic the sparse and asynchronous activation of the animal retina, offering advantages such as low latency and low computational load in ...
IEEE

Contrastive Graph Convolution Network With Skip Connections for Few-Shot Hyperspectral Image Classification

Abstract: Graph convolution networks (GCNs) have achieved impressive results for few-shot hyperspectral image (HSI) classification. However, current methods focus on migrating labels from support ...
GitHub

error in inference process (no valid convolution algorithms available in CuDNN)

error in inference process (no valid convolution algorithms available in CuDNN) #25 New issue ...