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Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

Domestic Supercomputer Hits 2.16 EFLOP/s, Enabling 10,000× Remote‑Sensing Compression

The D2AR generative compression framework leverages historical Earth‑observation priors and a dual‑decoupled asymmetric design to achieve exascale training at 2.16 EFLOP/s on a domestic Armv9 CPU supercomputer, scaling to 20,480 nodes and delivering up to 10,000× data reduction while preserving scientific utility.

Armv9 supercomputerdata reductionexascale AI
0 likes · 8 min read
Domestic Supercomputer Hits 2.16 EFLOP/s, Enabling 10,000× Remote‑Sensing Compression
HyperAI Super Neural
HyperAI Super Neural
Sep 29, 2025 · Artificial Intelligence

8 Popular Remote Sensing Object Detection Datasets with One-Click Downloads

This article presents a curated list of eight widely used remote sensing object detection datasets covering indoor scenes, landslides, drone imagery, crop diseases, safety vests, human fractures, urban issues, and plant diseases, each with size estimates and direct download links for researchers.

AIcomputer visiondatasets
0 likes · 10 min read
8 Popular Remote Sensing Object Detection Datasets with One-Click Downloads
AI Frontier Lectures
AI Frontier Lectures
Jun 10, 2025 · Artificial Intelligence

Can One Model Master All Remote Sensing Tasks? Introducing the TSSUN Framework

This paper presents the Temporal‑Spectral‑Spatial Unified Network (TSSUN), a flexible deep‑learning architecture that simultaneously handles semantic segmentation, semantic change detection, and binary change detection across heterogeneous remote‑sensing inputs, achieving state‑of‑the‑art performance without task‑specific retraining.

TSSUNattention mechanismdeep learning
0 likes · 15 min read
Can One Model Master All Remote Sensing Tasks? Introducing the TSSUN Framework
AIWalker
AIWalker
Mar 1, 2025 · Artificial Intelligence

Lightweight Remote Sensing Backbone LSKNet and Strip R-CNN: Design, Benchmarks, and Open‑Source Release

The NK‑Remote repository introduces LSKNet and Strip R‑CNN, two lightweight yet powerful models for remote‑sensing object detection that dynamically adjust receptive fields and combine square‑and‑strip convolutions, achieving state‑of‑the‑art performance on benchmarks such as DOTA, FAIR1M, HRSC2016, and DIOR.

JDetLSKNetStrip R-CNN
0 likes · 9 min read
Lightweight Remote Sensing Backbone LSKNet and Strip R-CNN: Design, Benchmarks, and Open‑Source Release
AntTech
AntTech
Jan 24, 2025 · Artificial Intelligence

High‑Resolution Hyperspectral Intelligent Fusion Imaging: Background, Key Achievements, and Future Directions

The talk presents a comprehensive overview of high‑resolution hyperspectral intelligent fusion imaging, covering its background, three major research contributions—including tensor‑coupled imaging mechanisms, structured low‑rank tensor models, and model‑guided low‑rank fusion methods—and outlines future research challenges and directions.

AIfusion imaginghyperspectral imaging
0 likes · 14 min read
High‑Resolution Hyperspectral Intelligent Fusion Imaging: Background, Key Achievements, and Future Directions
AntTech
AntTech
Mar 1, 2024 · Artificial Intelligence

Ant Group Unveils SkySense: 2.06‑Billion‑Parameter Multimodal Remote‑Sensing Foundation Model Accepted at CVPR 2024

Ant Group introduced SkySense, a 2.06‑billion‑parameter multimodal remote‑sensing foundation model that outperformed 18 international rivals across 17 benchmark tasks, was accepted to CVPR 2024, and aims to support applications such as agriculture, urban planning, and disaster response.

Ant GroupCVPR 2024Foundation Model
0 likes · 6 min read
Ant Group Unveils SkySense: 2.06‑Billion‑Parameter Multimodal Remote‑Sensing Foundation Model Accepted at CVPR 2024
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Nov 24, 2022 · Cloud Native

How Young Developers Are Putting AI Code on Satellites with Cloud‑Native Platforms

A nationwide “Code to Space” competition, backed by Huawei Cloud, Beijing University of Posts and Telecommunications, and others, invited student teams to develop cloud‑native, AI‑driven satellite applications, resulting in award‑winning projects like CoStar that dynamically split neural‑network models between edge and cloud, boosting efficiency and reducing bandwidth.

cloud-nativeremote sensingsatellite computing
0 likes · 12 min read
How Young Developers Are Putting AI Code on Satellites with Cloud‑Native Platforms
Code DAO
Code DAO
Dec 23, 2021 · Artificial Intelligence

Permutation‑Invariant PIUnet Boosts Multi‑Temporal Satellite Image Super‑Resolution

The article explains how satellite images suffer from limited spatial resolution, why the ordering of multi‑temporal frames is irrelevant, and how the PIUnet model introduces permutation‑invariant equivariant layers to achieve state‑of‑the‑art super‑resolution efficiently, winning the AI4EO challenge.

PIUnetSatellite Imagerydeep learning
0 likes · 6 min read
Permutation‑Invariant PIUnet Boosts Multi‑Temporal Satellite Image Super‑Resolution
Python Programming Learning Circle
Python Programming Learning Circle
Aug 17, 2021 · Fundamentals

Python Implementation for Remote Sensing Ecological Index Calculation

This article presents a Python implementation for calculating remote sensing ecological indices—including wetness, greenness, temperature, dryness, and a combined ecological index—using Landsat imagery, detailing the code, usage instructions, and methods for reading data, computing indices, normalizing results, and saving output images.

Ecological IndexLandsatimage processing
0 likes · 7 min read
Python Implementation for Remote Sensing Ecological Index Calculation