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Visão Computacional

Papers, modelos e datasets em alta no Hugging Face, além do blog oficial — com leitura editorial em português.

todas LLMs & Texto Geração de Imagem Visão Computacional Áudio & Voz Multimodal Dados & Embeddings Robótica & RL
Blog Visão Computacional

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition

arXiv:2607.00358v1 Announce Type: new Abstract: Electroencephalogram (EEG) captures endogenous brain activity with high temporal fidelity and holds substantial promise for precise emotion decoding. However, channel redundancy and pronounced inter-subject variability remain key obstacles to scalable generalization. To address these limitations, we propose a novel framework termed PRioritized channel Importance with Semi-supervised doMain adaptation (PRISM), enabling label-efficient cross-subject ...

02.07.2026
Blog Visão Computacional

From Technical Metrics to User Perception: A User Study of a Multimodal Human-Robot Interaction System for Object Detection and Grasping

arXiv:2607.00530v1 Announce Type: new Abstract: Improvements in the technical performance of human--robot interaction (HRI) systems do not automatically translate into differences that human users can detect during live interaction. This paper investigates whether a 15 percentage point gain in end-to-end task success (from 75% in a multimodal baseline system to 90% in an improved configuration identified through a prior ablation study) is sufficient to produce consistent and measurable differenc...

02.07.2026
Blog Visão Computacional

Enhancing Oracle Bone Inscription Recognition via Multi-Scale Layer Attention

arXiv:2607.00057v1 Announce Type: new Abstract: Oracle Bone Inscriptions (OBIs) recognition plays a crucial role in understanding ancient Chinese culture. However, accurately recognizing OBIs remains highly challenging due to their complex, irregular, and often degraded shapes. Traditional methods rely on expert knowledge and manual analysis, which are time-consuming and error-prone. Although deep learning has greatly advanced general image recognition, existing methods struggle to capture the f...

02.07.2026
Blog Visão Computacional

Trust the Prior (or Not): Uncertainty-Aware Abdominal Aortic Aneurysm Segmentation

arXiv:2607.00201v1 Announce Type: new Abstract: Robust segmentation of intraluminal thrombus is critical for risk assessment in Abdominal Aortic Aneurysm, yet it remains challenging due to heterogeneous thrombus features and low contrast with surrounding non-enhanced tissues. Domain shifts induced by different Computed Tomography Angiography (CTA) protocols further inhibit multi-center generalization of deep learning models. To address these challenges, we propose a patient-specific framework th...

02.07.2026
Blog Robótica & RL

Memory-Native Non-Terrestrial Networks for Embodied Intelligence

arXiv:2607.00029v1 Announce Type: new Abstract: Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in wilderness to leverage cloud resources or report critical information to remote centers. However, the synergy is nontrivial due to the highly-dynamic, resource-constrained, topology-varying, and task-oriented environment. Existing memoryless NTN protocols become inefficient, since the decisions are driven by local channel conditions and...

02.07.2026
Meta's non-invasive brain-to-text AI is closing the gap with surgical implants
Blog LLMs & Texto

Meta's non-invasive brain-to-text AI is closing the gap with surgical implants

Meta's FAIR AI team uses Brain2Qwerty v2 to translate brain activity into typed sentences, with no implants or surgery required. The system reads magnetic signals outside the skull and reconstructs what a person is typing. Clinical use for paralyzed patients is still a long way off, but accuracy keeps improving with every additional recording. AI agents that wrote their own code helped with the optimization. The article Meta's non-invasive brain-to-text AI is closing the gap with surgical implan...

01.07.2026
Blog Visão Computacional

Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos

arXiv:2606.31007v1 Announce Type: new Abstract: Vision foundation models such as SAM 3 can provide transferable object-level structure across diverse surgical video conditions, but segmentation outputs do not explicitly encode the action-conditioned semantics that define functional surgical landmarks. Estimating instrument extent and geometry differs from localizing the tip or anchor relevant to clipping, grasping, or dissecting. We investigate vision foundation model-enabled sparse action-aware...

01.07.2026
Blog Áudio & Voz

Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection

arXiv:2606.31186v1 Announce Type: new Abstract: Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in pathological language. We propose a Multi-View Gated Graph Attention Network that transcribes audio via Automatic Speech Recognition (ASR) to construct semantic, dependency, and co-occurrence graphs, characterizing speech through a "content-structure-flow" framework. Notably, th...

01.07.2026
Blog Visão Computacional

Simple Supervision Is Hard to Beat: A Bitter Lesson from Sparse Target Labels in Domain-Adaptive Object Detection

arXiv:2606.30795v1 Announce Type: new Abstract: Source-free domain adaptive object detection adapts a source-trained detector to an unlabeled target domain, typically through teacher-student self-training with pseudo-labels. We revisit this setting when a small, uniformly sampled subset of target images is labeled. We introduce Random-Target Supervised Mixing (RTSM), a simple anchor that incorporates these annotations through a supervised detection loss while leaving the original unlabeled adapt...

01.07.2026
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