“This article discusses the implementation of tokenization and word segmentation.”

“"CamVidは、正式名称「Cambridge-driving Labeled Video Database」の略称で、自動運転やロボティクス分野におけるセマンティックセグメンテーション（画像のピクセル単位での意味分類）の研究・評価に用いられる標準的なベンチマークデータセッ..."”

“Artificial intelligence and big data are reshaping digital marketing by providing new insights into consumer behaviour.”

“OFL-SAM2 achieves state-of-the-art performance with limited training data.”

“The paper introduces a learnable feature embedding for segmentation in Gaussian primitives and a novel 'Embedding-to-Label' process.”

“EVOL-SAM3 not only substantially outperforms static baselines but also significantly surpasses fully supervised state-of-the-art methods on the challenging ReasonSeg benchmark in a zero-shot setting.”

“The paper's key finding is that existing SOTA 3D semantic segmentation models (FPT, PTv3, OA-CNNs) show significant limitations when applied to the created post-disaster dataset.”

“SliceLens achieves state-of-the-art performance, improving Precision@10 by 0.42 (0.73 vs. 0.31) on FeSD, and identifies interpretable slices that facilitate actionable model improvements.”

“The paper establishes TEDPara and YTSegPara as the first benchmarks for the paragraph segmentation task in the speech domain.”

“Analyzing 1.4 million customer transactions across seven markets, our approach reduces false positive and false negative rates to 4.64% and 11.07%, substantially outperforming single-institution models. The framework prevents 79.25% of potential losses versus 49.41% under fixed-rule policies.”

“The paper's core finding is the ability to generate a high-quality, contextually grounded 3D mesh from a single RGB-D image in under one second.”

“The system achieves 87.7% frame-level accuracy in action segmentation that increased to 93.62% with post-processing, and an average classification accuracy of 76% in replicating expert assessments across all skill aspects.”

“The Dermatology Assessment Schema (DAS) is a novel expert-developed framework that systematically captures clinically meaningful dermatological features in a structured and standardized form.”

“CERES implements dual-modal causal intervention: applying backdoor adjustment principles to counteract language representation biases and leveraging front-door adjustment concepts to address visual confounding.”

“MambaSeg achieves state-of-the-art segmentation performance while significantly reducing computational cost.”

“ARM learns to adaptively fuse hierarchical features. It employs a semantically-guided cross-attention block, using robust deep features (K, V) to select and refine detail-rich shallow features (Q), followed by a self-attention block.”

“BATISNet outperforms existing methods in tooth integrity segmentation, providing more reliable and detailed data support for practical clinical applications.”

“This article discusses the use of Gemini 2.5 Flash for image segmentation, focusing on identifying and isolating objects within an image.”

“DGC achieves background-tissue separation (mean IoU 0.925) and demonstrates unsupervised disease detection through navigable semantic granularity.”

“The model achieves an IoU of 0.9130 validating the success and efficacy of the "temporal-first" strategy.”

“RSAgent achieves a zero-shot performance of 66.5% gIoU on ReasonSeg test, improving over Seg-Zero-7B by 9%, and reaches 81.5% cIoU on RefCOCOg, demonstrating state-of-the-art performance.”

“The Hilbert-VLM model achieves a Dice score of 82.35 percent on the BraTS2021 segmentation benchmark, with a diagnostic classification accuracy (ACC) of 78.85 percent.”

“GASeg achieves state-of-the-art performance on four benchmarks, including COCO-Stuff, Cityscapes, and PASCAL, validating our approach of bridging geometry and appearance via topological information.”

“GCA-ResUNet achieves Dice scores of 86.11% and 92.64% on Synapse and ACDC benchmarks, respectively, outperforming a range of representative CNN and Transformer-based methods.”

“The system achieved a frame-level action segmentation accuracy of 92.4% and an overall skill classification accuracy of 85.5%.”

“The method achieved superior performance compared to state-of-the-art methods on BraTS2020, with average Dice scores of 87.55, 79.36, and 62.67 for WT, TC, and ET, respectively, across fifteen missing modality combinations.”

“sCTs achieved 99% structural similarity and a Frechet inception distance of 1.01 relative to real CTs. Skull segmentation attained an average Dice coefficient of 85% across seven cranial bones, and sutures achieved 80% Dice.”

“The paper highlights the development of a new surface segmentation algorithm that incorporates human input and the use of continuous visual feedback to refine the robot's learned model.”

“The model reaching 96.23% accuracy, 95.58% F1-score and 94.83% specificity.”

“A last-layer Laplace approximation yields uncertainty estimates that correlate well with segmentation errors, indicating a meaningful signal.”

“SOFTooth achieves state-of-the-art overall accuracy and mean IoU, with clear gains on cases involving third molars, demonstrating that rich 2D semantics can be effectively transferred to 3D tooth instance segmentation without 2D fine-tuning.”

“The method 'achieves higher reconstruction quality around object edges compared to existing 2DGS methods.'”

“The best classification model (VIPRnet) achieved a validation accuracy of 99%.”

“The results demonstrate that SecureBank significantly improves automated attack handling and accelerates identity trust adaptation while preserving conservative and regulator aligned levels of transactional integrity.”

“Lung masking should be treated as a controllable spatial prior selected to match the backbone and clinical objective, rather than applied uniformly.”

“LAM3C achieves higher performance than the previous self-supervised methods on indoor semantic and instance segmentation.”

“Co2S, a stable semi-supervised RS segmentation framework that synergistically fuses priors from vision-language models and self-supervised models.”

“The title itself provides the core concept: using spatial awareness and symmetric alignment to improve text-guided medical image segmentation.”

“SwinTF3D achieves competitive Dice and IoU scores across multiple organs, despite its compact architecture.”

“”

“The article likely starts by introducing the recent advancements in image recognition, specifically focusing on Meta's SAM series.”

“GPT-5-mini reaching a best average F1 of 72.4 across sentence-level and freetext segmentation.”

“The paper proposes an active learning algorithm with Fisher Information that quantifies the informativeness of candidate views with respect to both semantic Gaussian parameters and deformation networks.”

“The key idea is to represent the decomposed 4D scene with the Freetime FeatureGS and design a streaming feature learning strategy to accurately recover it from per-image segmentation maps, eliminating the need for video segmentation.”

“It includes a simple version where I did not include any textual segmentation... and one with SAM3 / SAM2 nodes.”

“The paper proposes a unified hybrid memory framework that explicitly decomposes memory into short-term appearance memory and long-term distractor-resolving memory.”

“The paper reports high Dice Similarity Coefficients (DSC) for whole tumor (WT), enhancing tumor (ET), and tumor core (TC) across multiple BraTS datasets, indicating improved segmentation accuracy.”

“Is there a way to use such precise segmentation maps (together with some text/json file describing what each color represents) to communicate complex scene layouts in a structured way?”

“The paper argues for an eojeol based constituency representation, with morphological segmentation and fine grained part of speech information encoded in a separate, non constituent layer.”

“The results demonstrate consistent segmentation across diverse geometries and reveal coordinated epithelial-lumen remodeling, breakdown of morphometric homeostasis during collapse, and transient biophysical fluctuations during fusion.”