Cloud Removal
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ATT-CR: Adaptive Triangular Transformer for Cloud Removal
arXiv:2606.05999v1 Announce Type: new Abstract: Cloud removal aims to accurately reconstruct the ground objects obscured by clouds in remote sensing images. Existing Transformer-based methods utilizing self-attention have shown impressive results by effectively modeling long-range dependencies in cloudy images. However, they suffer from the following issues: 1) the high computational complexity of self-attention limits scalability; 2) treating both cloudy and clean pixels as valid within the...
IB-HFN: Information Bottleneck-Driven SAR-Optical Fusion Network for High-Fidelity Cloud Removal
arXiv:2606.09347v1 Announce Type: new Abstract: Synthetic aperture radar (SAR)-assisted optical cloud removal aims to recover surface information obscured by clouds in optical remote sensing images by exploiting complementary SAR observations. Existing multimodal fusion methods typically rely on direct spatial concatenation and pixel-wise supervision, which can propagate SAR speckle noise into optical reconstruction and lead to over-smoothed results. To address these limitations, we propose...
Demand-Driven Vulnerability Detection for Cloud Security Posture Management: Removing Human Rule Authoring from the Disclosure-to-Protection Critical Path
arXiv:2606.07957v1 Announce Type: new Abstract: Cloud Security Posture Management (CSPM) systems detect known vulnerabilities by maintaining a rule set, distributing it to customers, and evaluating it against periodically-collected asset inventories. To our knowledge, in publicly documented architectures the rule set is environment-agnostic and curated centrally by the vendor; updates are batched into release cycles and shipped on a cadence ranging from hours to days depending on detection...
Deep Learning for Remote Sensing to Improve Flood Inundation Mapping
arXiv:2606.02310v1 Announce Type: new Abstract: Flooding is the most pervasive natural disaster worldwide. Timely and accurate flood inundation mapping are essential for informing disaster risk management. Optical satellite missions provide high-resolution, multispectral observations critical for flood detection and inundation mapping.
The Top New Features in Apple’s iOS 27 and iPadOS 27
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wolfSSL releases a new product; wolfCOSE a zero alloc C embbedded COSE stack
wolfCOSE is a lightweight C library implementing CBOR (RFC 8949) and COSE (RFC 9052/9053) using wolfSSL as the crypto backend. - Complete RFC 9052 message set: all six COSE message types, including multi-signer COSE_Sign and multi-recipientCOSE_Encrypt /COSE_Mac - Post-quantum signing: ML-DSA (Dilithium) at all three security levels - 40 algorithms across signing, encryption, MAC, and key distribution - Zero dynamic allocation: all operations use caller-provided buffers - Tiny footprint: 7.5...
Marvell Technology jumps almost 9% in premarket after news it will join the S&P 500 index
Marvell Technology was up almost 9% in premarket trading on Monday after it was announced that the AI chipmaker would be joining the benchmark S&P 500 index. The semiconductor company, which trades on the Nasdaq, will join the broad-market index on June 22 and will sit alongside the 500 leading companies in the U.S., S&P Global said in a press release on Friday. Marvell was last seen up 8.8% in premarket trading and is up 210% year-to-date.
RadiusFPS: Efficient Farthest Point Sampling on CPUs and GPUs via Spherical Voxel Pruning
arXiv:2606.06255v1 Announce Type: new Abstract: Point clouds are a primary sensory representation for robotic perception, underpinning LiDAR-based autonomous driving, simultaneous localization and mapping (SLAM), and navigation. Within these pipelines, Farthest Point Sampling (FPS) is the most well-known downsampling operator, as its uniform coverage preserves the geometric structure on which downstream perception relies. However, the large time complexity of classical FPS scales poorly with...
Cisco rolls out software tools to protect IT systems from AI agents
Cisco rolls out software tools to protect IT systems from AI agents SAN FRANCISCO, June 2 : Cisco Systems on Tuesday announced a new suite of software tools that businesses can use to build their own armies of bots known as AI agents, to protect their IT infrastructure against cybersecurity threats. Cisco's announcement comes as Anthropic is set to release its Mythos model in the coming weeks, an AI tool that some experts fear could be used by hackers to turbo-charge cyber attacks. Cisco...