「segmentation」の検索結果
216 件ultralyticsはYOLO(You Only Look Once)の技術を使用したオブジェクト検出ライブラリで、高い精度を提供している。
データラベル化と注釈化を行うためのツールです。
CoreNLPはJavaで開発されたNLPツールのセットであり、分割、文分割、名詞認識、パーシング、コorefence、感情分析などを行える。
stanzaは、さまざまな言語を処理するための言語処理用ライブラリです。
Tokenization is a fundamental component of modern language models: before a model sees data, its tokenizer has
Motivated by the expressive power of neural ordinary differential equations in flow-based generative modeling,
Deep-learning-based mass detectors usually downsample mammograms, trading fine image detail for lower computat
Reasoning vision-language-action (VLA) models pair physical control with natural-language rationales that supe
Speech watermarking is becoming a key defense for digital copyright and content authentication. Existing attac
Recent advances in large language models have enabled agentic systems that automate machine learning pipeline
Why do language models fail on long inputs? The common answer is length.
Parallel decoding speeds up masked diffusion language models by writing several tokens per forward pass. Publi
Chest radiography (CXR) diagnosis is critical for thoracic disease assessment, yet challenged by the need to i
Semi-supervised medical image segmentation aims to train reliable segmentation models using limited labeled da
Diffusion-based data augmentation has emerged as a powerful strategy for addressing data-scarce image classifi
Separating touching nuclei requires local boundary detail, while cell type classification requires broader mor
Foot ulcers are a leading cause of lower limb amputation, and the highest burden often falls on low and middle
Semi-supervised cardiac image segmentation aims to exploit abundant unlabeled images together with limited ann
Self-attention has become the standard for modern sequence modeling, enabling Transformers to model long-range
The corotation radius R_CR of a spiral galaxy marks the radius where the angular speed of the spiral pattern m
Hamilton-Jacobi (HJ) reachability provides certified backward reachable tubes (BRTs) for safety-critical robot
supervisionは、機械学習技術を活用して、ユーザー独自のコンピュータビジョンツールを作成することができる。
CVATは、機械学習用の業界標準のデータエンジンです。さまざまなスケールのチームが使用し、さまざまなスケールのデータに対応しています。
イメージを注釈するツール。ポリゴン、長方形、円、線、点などを注釈することができる。
Graph forecasting systems often rely on prediction intervals to quantify uncertainty across connected location
Neural controlled differential equations (Neural CDEs) evolve hidden states along continuous paths constructed
Retaining predictive gains can require persistent errors in a model's response to interventions. For determini
Mapping the three-dimensional distribution of dark matter is key to tracing the growth of cosmic structure. Tw
In this paper, we study when two parties should pool their data to train a machine learning model. Two agents,
Hybrid models and neural differential equations (NDEs) are becoming increasingly important for modelling physi
Hamiltonian neural networks provide a principled framework for learning conservative dynamics. A scalar Hamilt
Recent language model (LM) safety failures have largely been studied as disparate phenomena. In agentic misali
Suicide prevention remains a critical public health challenge, and electronic health records (EHRs) provide an
Calibrated multiaccuracy asks that a predictor be globally calibrated and multiaccurate with respect to a boun
Inverse Reinforcement Learning (IRL) aims to recover expert rewards that transfer across environments with dif
In node selection tasks, the goal is to identify a single unknown target node in a graph. We consider probabil
Artificial Intelligence, and Machine Learning in general, is becoming pervasive across all domains and discipl
Diffusion models trained on distinct datasets can produce highly similar samples when prompted with the same n
An aggregate task score does not distinguish failures of scheduling, state retention, and candidate selection.
Recourse-aware learning trains models so that people who receive an adverse decision can reverse it with an af
On July 1, 2025, Vietnam reduced its 63 provinces to 34, abolished its 696 districts, and replaced its 10,035
There are many causal discovery algorithms, but few guiding principles for choosing between them. Methods are
Time-series segmentation, studied as either Change Point Detection (CPD) or State Detection (SD), underpins a
Pose-driven human video diffusion animates a person from a single reference image and a target pose sequence,
While state of the art for image and video generation, the fundamental reasons for the effectiveness of genera
Fusing independently normalized attention heads can increase the number of explicit key-value entries, or atom
Dynamic regret measures an online learner against a moving comparator, and standard analyses assume the learne
Learning to stabilize an unknown continuous-time stochastic linear system is a central problem in control theo
The Musical Metaverse (MM) enables geographically distributed musicians, audiences, sound engineers, and AI ag
A stored experience may answer one future question and offer little help with another. We measure this task-co
Financial research agents can generate and monitor trading rules faster than a human can document the resultin
Self-supervised learning inherits the coverage of its source data. When an unlabeled corpus is long-tailed, th
Novel imaging modalities promise improved diagnostics, but AI development is constrained by scarce training da
The literature on autonomous weapon systems (AWS) includes many proposed definitions for these (types of) syst
Kolmogorov-Arnold Networks (KANs) have recently been proposed as a promising alternative to Multi-Layer Percep
Reaction data underpin machine learning for reaction prediction, condition recommendation, and retrosynthetic
Law changes over time. A court decides a case under the law in force on that day, and legal QA benchmarks grad
WhatsApp lets a business send free-form messages only within 24 hours of a user's last message; outside this c
Language models with similar benchmark accuracy can succeed on different items. Overall scores do not show whe
Cross-Domain Few-Shot Segmentation (CD-FSS) aims to segment objects from unseen domains using only a few annot
Transfer learning from pretrained backbones has become standard practice in multi-sensor computer vision---yet
Source-only domain generalization (DG) for remote sensing semantic segmentation seeks reliable predictions in
Semantic change detection in remote sensing aims to identify and characterize land-cover transitions observed
Fingerspelling - the sequential signing of letters that compose proper names, technical terms, and out-of-voca
Accurate mapping of shallow-water environments using unmanned aerial vehicle (UAV) imagery is challenged by wa
Image-text corpora contain copies of one image, captions that describe one image in different ways, captions r
We present a GPU-native volumetric-video system for real-time reconstruction of graphics-compatible textured t
Adapting features before upsampling can improve dense prediction, but the gains may arise from changes in feat
Urban photogrammetric point clouds are commonly processed as local 3D patches, limiting the context available
3D Gaussian Splatting (3DGS) enables photorealistic novel- view synthesis with real-time rendering, yet fine-g
Semantic granularity, which refers to the levels at which visual representations organize image content into m
Joint nuclei instance segmentation and classification requires precise boundaries and neighborhood information
Widespread image sharing on social media has increased the need for visual privacy recognition to identify ina
3-D road anomaly segmentation is essential for risk-aware perception in autonomous driving. Its central challe
Effective polyp segmentation in colonoscopy images is crucial for early detection of colorectal cancer, a lead
Cooperative perception (CP) requires substantial communication bandwidth to exchange sensing information among
Reinforcement learning (RL) post-training improves the single-sample quality of visual generative models, but
Cross-view object correspondence (CVOC) aims to establish associations of the same target between query and se
Understanding how cells respond to perturbations over time is central to cell biology and drug discovery. Live
A mobile manipulator asked to "put the toys away in the toy box" must decide which objects are toys and which
World action models (WAMs) jointly generate actions and imagined futures, but a plausible prediction need not
Conventional robot arms can be extremely heavy compared with the everyday objects they manipulate, creating a
Overactuated multirotors can produce the same wrench with many rotor-speed combinations, some of which leave t
Many manipulation goals are easier to visualize than to specify numerically through explicit geometric constra
The Generalized Singular Value Decomposition (GSVD) is a central tool for comparing two linear operators that
Hierarchical control scales robot behavior by separating task-level planning from low-level control. In dynami
Robot policies still fail at everyday manipulation: an unfamiliar task, an object never held before, a scene t
To design platforms for multi-operator mobility markets coordinating their operations or infrastructure to sup
Progress in AI is often measured by what a single model can do on its own. Yet teams of AI agents are starting
セマンティックシーケンス分割モデルのライブラリです。
We consider classification in high-dimensional feature spaces where only a vanishing fraction of features are
Spectral shrinkage encompasses a broad family of estimators for high-dimensional linear regression that regula
We study finite-horizon reinforcement learning with a safety constraint on the probability of reaching a failu
Tensor factor models provide low-dimensional representations of tensor-valued observations while preserving th
Convex regression provides a flexible nonparametric estimation framework while incorporating appropriate shape
Conditional sampling is central to Bayesian inference, generative modeling, and causal inference: given a join
We present a generalized variational approach for constructing energy-stable macroscopic partial differential
Scaling laws predict the outcome of large, expensive training runs by extrapolating trends from smaller, cheap
Key-value (KV) cache eviction methods rank tokens by attention scores, and each layer scores its own cache. To
Coding agents can destroy data, leak secrets and message the wrong person faster than a human can review. Coul
Factual recall in language models is typically framed as retrieving a factual association: a subject--relation
Temporal Knowledge Graph Question Answering (TKGQA) requires language model agents to retrieve evidence, selec
We present See, Think, Use, a protocol that traces each answer of a vision-language model to perception, reaso
Robust segmentation of biomedical images remains challenging primarily due to ill-defined object boundaries. A
Diffusion driving vision-language-action models repeatedly execute the backbone at every denoising stage, incu
Vision-language-action (VLA) models predict chunks of future actions, yet deployed robots waste time in two wa
Prediction errors from video world models are often treated as physical surprise, but they can also reflect ap
YOLOv5という物体検出アルゴリズムをPyTorchから他の言語に変換できるライブラリ。
このライブラリは、コンピューター ビジョンのための高度なAI解釈と可視化ソリューションです。このライブラリは、CNN、ビジョン トランスフォーム、分類、物体検出、分割、画像類似度など、さまざまなコンピューター ビジョンの
Bayesian inverse problems require both informative prior models and computationally feasible posterior inferen
Learning from extensive longitudinal clinical records--spanning repeated encounters, evolving conditions, and
Replacing the matrix in an iteration with random low-rank matrices can reduce the cost of matrix-vector multip
Machine learning can screen far more candidates than can be experimentally validated, creating a need for sele
Calling a tool through generated text adds decoding steps, even when the computation itself is short. We study
Post-trained language models fabricate citations at high rates. We ask whether that is reward hacking: scoring
Simulation-based VLA evaluation often treats matching task, seed, and episode identifiers as sufficient eviden
Accurate posture feedback is essential for precise control of continuum robots. Off-the-shelf bend sensors mea
Imitation policies inherit the operator's pace, and re-timing the demonstrations to run faster works only unti
We study finite sample guarantees for transport based mutual information estimation. Mutual information can be
Concept erasure is a prominent approach to achieving fairness in machine learning through the removal of sensi
Large generative models are commonly trained on data collected from the open web, which may contain data produ
Distributionally robust optimization (DRO) minimizes worst-case risk under distributional uncertainty, but its
Sampling from Boltzmann distributions is a fundamental problem in physics, chemistry, and biology. We introduc
Implicit priors given by Gaussian denoisers successfully regularize a wide range of inverse problems in approa
Flow matching depends critically on the coupling used to pair source and target samples. Optimal transport (OT
We study the general problem of estimating $D(\dde(S))$, the probability that an unknown distribution $D$ assi
We study whether a language model can help design controllers whose behavior can be formally checked. In proof
Held-out validation loss is the standard offline signal for choosing checkpoints and comparing models, but its
Uncontrolled hemorrhage remains a leading cause of preventable trauma mortality. Timely intervention is not al
How to reuse a pretrained locomotion policy for precise loco-manipulation is still an open problem. We propose
Autonomous surface vessels operating in urban waterways must coordinate with other vessels in confined spaces
We study the online fair division of indivisible chores among $n$ agents under upgrade recourse, where earlier
Motivated by a broad literature in psychology, organizational behavior, and matching markets, we introduce str
Statistical contracts reward experimenters according to the evidence produced by a costly study, so the reward
Modern data analysis pipelines increasingly rely on large datasets assembled through retrieval, scraping, auto
We study high-dimensional integration on bounded convex domains. Given a non-negative integrand $r$, the goal
Predictive models trained at well-resourced data-rich institutions often fail when deployed in new populations
We consider the problem of finite-sample identification of an unknown LTI system from a finite hypothesis clas
We study high-dimensional nonparametric regression under multisource covariate shift, where $\mathrm J$ source
In this work, we formalize the concept of intrinsic dimension of objective landscapes introduced in Li et al.
A streaming estimator must compute from the evidence that fits in memory. We determine when storing an accurat
Reinforcement learning with verifiable rewards (RLVR) makes a language model solve more problems on the first
Parameter estimation and classification in binary logistic regression deteriorate severely when the number of
Hardware-accelerated spiking neural networks (SNNs) implemented on memristive crossbar arrays offer significan
Classical theory predicts that irrational traders lose money to rational traders and are eventually driven out
In a duopoly with captive and contested consumers, I characterize every pair of consumer and producer surplus
Vision-Language-Action (VLA) models have demonstrated promising capabilities in robotic manipulation by integr
Do research agents have taste, the judgment of which experiments are worth running before their outcomes are k
Agentic image editors decompose complex requests into steps, but when a step fails, they mostly retry with the
We present PhysInsert, a framework for physically plausible reference-based object insertion that jointly adap
Learning independence is fundamental to statistical inference and machine learning, yet learning independence
Particle Gibbs samplers with backward sampling are widely used for sampling the smoothing distribution of stat
Allowing for small fraction of errors in retrieved stored binary patterns, Hopfield-Hebbian neural network (NN
When exact probabilities cannot be computed, \emph{density ratio estimation (DRE)} is a key subroutine in the
Can a Watershed transform, the classical tool of morphological segmentation, be placed at the end of a deep ne
Music audio generation spans instrumental clips, full songs with vocals, edits of existing recordings, and sys
Humans routinely consume multimodal content, where textual and visual information is naturally interleaved. Al
We present EasyProver, a Lean proving system built from recursive agents with isolated contexts, asynchronous
Generative flows can admit different velocity fields that induce the same continuous marginal evolution but be
An input skip can reduce reconstruction error while leaving a model's distribution of new samples unchanged. F
Density estimation with generative models is a common task in the physical sciences, for example in background
We study the computational limits of clustering $n$ observations drawn from a mixture of $K$ isotropic distrib
Model discrepancy may prevent a single calibration parameter from reproducing a physical response across the c
Mutual information (MI) is fundamental to representation-learning analysis in deep networks, but in high dimen
Dimension-reduction methods such as PCA identify a subspace capturing most of the variation in the data, but n
We describe the agent we submitted to the GLEE Competition, which plays bargaining, negotiation, and persuasio
Token systems support repeated service exchange without monetary transfers, but their viability depends on the
We study facility location in multidimensional normed spaces with the objective of minimizing social cost, the
We develop a unified framework for assortment optimization and matching under multinomial logit (MNL) choice,
We study fair division of uncertain items, where the utility of each item is a random variable whose realizati
We study the order-selection prophet inequality. A gambler knows the distributions of independent nonnegative
An action seen once and the same action seen three times receive the same action-recognition label, so that su
Generating videos of a specific subject from a few reference images remains challenging when the camera reveal
Physical wave processors are constrained by diffraction, but the bandwidth of the mathematical functions they
We study online fair division of indivisible goods among $n$ agents with frequency predictions: before any goo
Benade et al. (EC 2024) introduced a semi-random model for non-additive fair division in which each agent star
Generative AI interfaces can insert sponsored content at multiple points in an answer, where click-through rat
Position auctions require assigning advertisers to positions and determining their display order. Under cascad
Attribution for a time-series forecaster should answer two questions that a feature-level scalar cannot: when
We study preemptive single-machine scheduling with predictions, where a prediction of the order of the jobs (o
The Perception-Adjusted Luce Model (PALM) introduced by by Echenique et al. (2018) is a sequential choice mode
In recent years, agentic orchestration has been widely applied to solve complex human tasks. However, existing
Neural network models are increasingly constructed from synapse-resolution connectomes, and the same circuit i
Bergemann, Brooks, and Morris (2015) characterize the consumer and producer surplus pairs that segmentation ca
We consider the problem of allocating indivisible goods to agents with additive valuations, under two classic
We study the best-response dynamics in games with random payoffs. We consider two-player bimatrix games, with
Edge medical segmentation must reconcile small model size, high accuracy, and fast inference. TernScope addres
In the classical necklace splitting problem, beads of different colors lie on a line, and the goal is to divid
Architectural and structural design optimization in parametric software affords about a thousand evaluations o
Networks of repeated neural modules with delayed neighbour coupling need stability guarantees for every number
Web platforms organize collective work, including content review and community maintenance, that imposes heter
On neuromorphic chips, spiking neural networks (SNNs) consume far less energy than artificial neural networks
Digital marketplaces increasingly earn revenue from transaction commissions and seller-facing data services. S
To facilitate the solving of complex problems, evolutionary multitask optimization is regarded as a promising
Advanced persistent threats (APTs) are a major concern in federated learning (FL) deployments in critical sect
Solving imperfect-information games at scale rests on counterfactual regret minimization with the regret match
Face image quality assessment (FIQA) estimates the utility of a face image for automated face recognition and
Exploiting temporal information in datasets with high temporal dependencies (such as spoken keyword recognitio
Engineering design tools increasingly embed optimizers as ready-made components that users select by algorithm
Pairwise comparison data are a standard supervision signal in preference learning, but disagreement in such da
In a repeated Stackelberg security game, a defender commits in every round to a randomized allocation of its r
We resolve the problem of unweighted online stochastic matching with a known arrival law by establishing its o
We prove that computing a complete contiguous $\varepsilon$-envy-free cake allocation is PPAD-complete for nor
We give new mechanisms for combinatorial auctions in the offline, secretary, and prophet-with-samples models.
We study the \emph{voter model with opinion graph}, a generalization of the standard (pull) voter model that a
Generating an image with a diffusion or flow-matching model typically involves integrating a velocity field fo
A fixed network of McCulloch-Pitts threshold units with weights in {-1,0,1} can hold other threshold networks
Process-induced warpage, ceramic stress and solder strain limit the reliability of insulated-gate bipolar tran
Variational quantum algorithms turn choices of Hamiltonian, ansatz, and parameterization into a classical nonc
Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from
Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying
A reliable assessment of an optimizer robustness requires tracking controlled changes in parameters to identif
Open-pit mining operational planning involves allocating limited resources while satisfying production, equipm
A novel discovery is one which is both useful and surprising: a generative model's output is a useful discover
Connectome models of the fly nerve cord generate walking-like motor rhythms, but oscillation alone does not sh
Stochastic cell updates are often used throughout the life of a neural cellular automaton (NCA), from backprop