TMCnet

WiMi Studies Hybrid Quantum-Classical Inception Neural Network Model for Image Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") ...

WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification

Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
EurekAlert!

To know what you do not know: An evidential deep learning framework for traffic classification

Traffic classification is a crucial task for network security. One of the most difficult challenges is to accurately identify the traffic of unknown applications as well as discriminate the known ...
Semiconductor Engineering

Using Deep Learning ADC For Defect Classification For Automatic Defect Inspection

In traditional semiconductor packaging, manual defect review after automated optical inspection (AOI) is an arduous task for operators and engineers, involving review of both good and bad die. It is ...
Science Daily

Researchers use artificial intelligence to boost image quality of metalens camera

Researchers have leveraged deep learning techniques to enhance the image quality of a metalens camera. The new approach uses artificial intelligence to turn low-quality images into high-quality ones, ...
News Medical

Camouflage detection boosts neural networks for brain tumor diagnosis

Neural networks trained with a camouflage detection step show enhanced accuracy and sensitivity in identifying brain tumors from MRI scans, mimicking expert radiologists. Study: Deep learning and ...