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Hjälporganisationer varnar: Massvält i Gaza https://www.dn.se/varlden/hjalporganisationer-varnar-massvalt-i-gaza/

Hjälporganisationer varnar: Massvält i Gaza
Över 100 hjälporganisationer, däribland Rädda Barnen och Läkare utan gränser, varnar för att massvält sprider sig i Gaza och de får…

RangeSAM: Leveraging Visual Foundation Models for Range-View repesented LiDAR segmentation
Paul Julius K\"uhn, Duc Anh Nguyen, Arjan Kuijper, Holger Graf, Dieter Fellner, Saptarshi Neil Sinha
https://arxiv.org/abs/2509.15886

RangeSAM: Leveraging Visual Foundation Models for Range-View repesented LiDAR segmentation
Point cloud segmentation is central to autonomous driving and 3D scene understanding. While voxel- and point-based methods dominate recent research due to their compatibility with deep architectures and ability to capture fine-grained geometry, they often incur high computational cost, irregular memory access, and limited real-time efficiency. In contrast, range-view methods, though relatively underexplored - can leverage mature 2D semantic segmentation techniques for fast and accurate predicti…

WGRAMMAR: Leverage Prior Knowledge to Accelerate Structured Decoding
Ran Wang, Xiaoxuan Liu, Hao Ren, Gang Chen, Fanchao Qi, Maosong Sun
https://arxiv.org/abs/2507.16768

WGRAMMAR: Leverage Prior Knowledge to Accelerate Structured Decoding
Structured decoding enables large language models (LLMs) to generate outputs in formats required by downstream systems, such as HTML or JSON. However, existing methods suffer from efficiency bottlenecks due to grammar compilation, state tracking, and mask creation. We observe that many real-world tasks embed strong prior knowledge about output structure. Leveraging this, we propose a decomposition of constraints into static and dynamic components -- precompiling static structures offline and in…

eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models
Paul R. B. Houssel, Siamak Layeghy, Priyanka Singh, Marius Portmann
https://arxiv.org/abs/2507.16241

eX-NIDS: A Framework for Explainable Network Intrusion Detection Leveraging Large Language Models
This paper introduces eX-NIDS, a framework designed to enhance interpretability in flow-based Network Intrusion Detection Systems (NIDS) by leveraging Large Language Models (LLMs). In our proposed framework, flows labelled as malicious by NIDS are initially processed through a module called the Prompt Augmenter. This module extracts contextual information and Cyber Threat Intelligence (CTI)-related knowledge from these flows. This enriched, context-specific data is then integrated with an input…

Leveraging Familiarity with Television to Enrich Older Adults' Engagement and Wellbeing: A Feasibility Study Using Video Probes
Shyama Sastha Krishnamoorthy Srinivasan, Mohan Kumar, Pushpendra Singh
https://arxiv.org/abs/2509.15618

Leveraging Familiarity with Television to Enrich Older Adults' Engagement and Wellbeing: A Feasibility Study Using Video Probes
The shift away from multigenerational families to nuclear families in India has created a growing need to support older adults living independently. While technology can help address this gap, older adults' limited exposure to newer technology restricts the adoption of such solutions. However, they remain comfortable with long-standing technologies like television (TV). This study explores their daily technology usage and challenges, aiming to determine whether TV can be leveraged to improve th…

"La vaccination contre la grippe reflète les inégalités sociales, selon un constat des Mutualités libres révélé lundi. Il y a en effet jusqu’Š 20% d’écart de couverture entre les plus et les moins favorisés."
https://bx1.be/categories/news/20-deca…

Une belle gang de toto ceux la
"La chambre de commerce réclame des « études impartiales » pour mesurer l’imprégnation de l’arsenic dans la population, explique M. Beaupré, qui dit ne pas savoir si la Direction de santé publique est impartiale."
Pis eux, sont impartiaux??

How Hurricane Resilience for Commercial Real Estate is Leveraging Drones and AI
CNBC - August 20, 2025
“As season after season produces more intense storms resulting in increasingly costly damage, facilities managers in commercial real estate are making property resilience a priority.”
https://www.

How hurricane resilience for commercial real estate is leveraging drones and AI
Site Technologies employs drones to help CRE facilities managers see where the vulnerabilities are in their properties and address them before storms hit.

DistillMatch: Leveraging Knowledge Distillation from Vision Foundation Model for Multimodal Image Matching
Meng Yang, Fan Fan, Zizhuo Li, Songchu Deng, Yong Ma, Jiayi Ma
https://arxiv.org/abs/2509.16017

DistillMatch: Leveraging Knowledge Distillation from Vision Foundation Model for Multimodal Image Matching
Multimodal image matching seeks pixel-level correspondences between images of different modalities, crucial for cross-modal perception, fusion and analysis. However, the significant appearance differences between modalities make this task challenging. Due to the scarcity of high-quality annotated datasets, existing deep learning methods that extract modality-common features for matching perform poorly and lack adaptability to diverse scenarios. Vision Foundation Model (VFM), trained on large-sc…

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique
Mohammad Asifur Rahim, Muhammad Nazmul Arefin, Md. Mizanur Rahman, Md Ali Hossain, Ahmed Moustafa
https://arxiv.org/abs/2507.15915

An empirical study for the early detection of Mpox from skin lesion images using pretrained CNN models leveraging XAI technique
Context: Mpox is a zoonotic disease caused by the Mpox virus, which shares similarities with other skin conditions, making accurate early diagnosis challenging. Artificial intelligence (AI), especially Deep Learning (DL), has a strong tool for medical image analysis; however, pre-trained models like CNNs and XAI techniques for mpox detection is underexplored. Objective: This study aims to evaluate the effectiveness of pre-trained CNN models (VGG16, VGG19, InceptionV3, MobileNetV2) for the early…