Abstract: Land-cover classification from multi-source remote sensing imagery requires the effective integration of complementary spatial and spectral information across heterogeneous modalities, which ...

Abstract: Due to the excellent feature extraction capabilities, deep learning has become the mainstream method for hyperspectral image (HSI) classification. Transformer, with its powerful long-range ...

Google has reportedly initiated the TorchTPU project to enhance support for the PyTorch machine learning framework on its tensor processing units (TPUs), aiming to challenge the software dominance of ...

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

This repo contains all my Deep Learning semester work, including implementations of FNNs, CNNs, autoencoders, CBOW, and transfer learning. I explored TensorFlow, Keras, PyTorch, and Theano while ...

Background: Gastric cancer (GC) is one of the most common malignant tumors and remains a leading cause of cancer-related mortality worldwide. Accurate classification of GC is critical for improving ...

Soumith Chintala, who co-created Meta Platforms’ open-source machine learning library PyTorch, is leaving the company, according to three people with direct knowledge of the matter. He joined Facebook ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. In this episode, Thomas Betts chats with ...

ABSTRACT: Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management. Conventional asset pricing models, such as the Fama-French three-factor ...

The choice between PyTorch and TensorFlow remains one of the most debated decisions in AI development. Both frameworks have evolved dramatically since their inception, converging in some areas while ...