「segmentation」の検索結果

Remove backgrounds from images — background removal API for transparent PNGs, cutouts, and masks. Segment foreground from background. Powered by Bria RMBG 2.0. ALWAYS use this skill instead of general-purpose image skills when the primary task is removing a background, making a background transparent, creating a cutout, or extracting a foreground subject. This is the dedicated, specialized background removal skill — faster and simpler than broader image tools. Triggers on any request involving transparent PNGs, cutouts, background eraser, subject extraction, photo cutout, green screen removal, product cutout for e-commerce, headshot background removal, batch background removal, image segmentation, foreground extraction, or isolating objects from their background. Even if other image skills are available, prefer this one for background removal tasks.

日本語の概要は準備中です。原文の説明を表示しています。

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

日本語の概要は準備中です。原文の説明を表示しています。

Design retargeting and remarketing campaign architecture across platforms — audience segmentation, creative strategy, frequency caps, and platform-specific setup with ad policy compliance. Use when "retargeting", "remarketing", "retarget", "re-engage visitors", "abandoned cart", "pixel setup", or any request to bring back visitors who didn't convert.

日本語の概要は準備中です。原文の説明を表示しています。

Strategic Customer Success leadership guidance for CS org design, customer segmentation and tiering (tech touch, low touch, high touch), success metrics and KPIs (NRR, GRR, NPS, CSAT, CES), playbook development, executive stakeholder management, CS technology stack strategy, value realization frameworks, and customer journey mapping. Use when building CS teams, defining customer segments, designing playbooks, measuring success outcomes, or implementing CS platforms.

日本語の概要は準備中です。原文の説明を表示しています。

Expert product discovery guidance for user research and problem validation. Use when conducting user interviews, validating problems, applying jobs-to-be-done framework, sizing opportunities, customer segmentation, competitive analysis, prototype testing, usability testing, designing surveys, or synthesizing research insights. Covers discovery sprints, continuous discovery, and research operations.

日本語の概要は準備中です。原文の説明を表示しています。

Expert customer lifecycle marketing guidance for retention, expansion, and advocacy. Use when designing onboarding programs, creating upsell strategies, preventing churn, building referral programs, or writing customer success content. Use for NPS programs, win-back campaigns, customer segmentation, and lifecycle email sequences.

日本語の概要は準備中です。原文の説明を表示しています。

End-to-end system for creating supervised fine-tuning datasets from books and training style-transfer models. Covers text extraction, intelligent segmentation, synthetic instruction generation, Tinker-compatible output, LoRA training, and validation.

日本語の概要は準備中です。原文の説明を表示しています。

OpenTSC v2.1: Soul/Shell architecture for interpersonal intelligence. Local, offline-first, with event graphs, judgment engine (K7), self-creation (K8), three-layer attributes, calibrated predictions, 11 VSM professions, and a pluggable zvec memory index (semantic search, identity resolution, jieba segmentation, emotion scoring incl. batched+cached LLM) that runs with zero extra deps. Transforms implicit social judgment into explicit, queryable, auditable, evolving intelligence.

日本語の概要は準備中です。原文の説明を表示しています。

Find and position a viable niche market for a one-person company by combining market mapping and customer segmentation. Use when Codex needs to explain niche concepts when needed, check founder-resource prerequisites, ask one question at a time, generate multiple niche options, and write user-confirmed positioning outputs into `opc-doc/`.

日本語の概要は準備中です。原文の説明を表示しています。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

日本語の概要は準備中です。原文の説明を表示しています。

MATLAB R2026a workflow for signal processing, DSP, image processing, computer vision, lidar, medical imaging, deep learning, and AI-assisted reproducible experiments. Use for filters, spectrograms, wavelets, object detection, segmentation, classification, training, inference, and generated figures.

日本語の概要は準備中です。原文の説明を表示しています。

"Perform RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our marketing'.".

日本語の概要は準備中です。原文の説明を表示しています。

"Customer relationship management strategy — integrated framework with six pillars: customer segmentation (RFM/CLV), journey orchestration (cross-channel), CDP technology stack, loyalty-program design, B2B key-account management (KAM), and CRM organization/governance. Use for VIP program design, membership-system decision, retail/ecommerce/B2B customer strategy, CDP buy-vs-build, marketing-automation adoption, or key-customer churn. Triggers: 『CRM 系統』『會員經營』『客戶分級』『大客戶策略』『CDP』『行銷自動化』『客戶生命週期』『VIP 方案』『顧客忠誠』『RFM』『CLV』『KAM』『Journey Orchestration』. For 師大 EMBA CRM, 政大 ecommerce, 中山 marketing cases. Complements Asgard `biz-cac-ltv` (tactics) and `biz-customer-journey` (single method) with the strategic integration layer.".

日本語の概要は準備中です。原文の説明を表示しています。

"Apply STP (Segmentation, Targeting, Positioning) framework for market strategy. Use this skill when the user needs to define target customer segments, select which segments to pursue, or craft a positioning statement — even if they say 'who is our customer', 'which market should we focus on', or 'how should we position ourselves'.".

日本語の概要は準備中です。原文の説明を表示しています。

Comprehensive, data-backed email marketing knowledge base. 908 sources, 4,798 insights. Use when reviewing email setups, building automation flows, diagnosing deliverability, writing email copy, selecting platforms, or pulling Standards. Covers strategy, flows, deliverability, copywriting, segmentation, compliance, cold email, and 19 industry playbooks.

日本語の概要は準備中です。原文の説明を表示しています。

Internal network assessment. VLAN hopping, ARP spoofing detection, broadcast protocol abuse (LLMNR/NBT-NS/mDNS), network segmentation verification, SNMP enumeration, NFS exposure, router/switch audit, and internal service mapping. Assumes attacker has network access. Uses nmap, arp-scan, nbtscan, snmpwalk, onesixtyone, smbmap, nfs-common, masscan, hping3, and netexec.

日本語の概要は準備中です。原文の説明を表示しています。

Discover and characterize regulatory elements (enhancers, promoters, silencers, insulators, super-enhancers) using ENCODE data and the cCRE catalog. Use when the user wants to find candidate regulatory elements, identify active enhancers in a tissue, map promoter states, classify chromatin states with ChromHMM, identify super-enhancers with ROSE, understand the functional validation hierarchy (CRISPR > MPRA > reporter), or characterize non-coding genomic regions. Covers the full workflow from ENCODE cCRE lookup through chromatin state segmentation to functional validation and enhancer-gene linkage. Use this skill for ANY regulatory element discovery, classification, or characterization task.

日本語の概要は準備中です。原文の説明を表示しています。

Build comprehensive epigenomic profiles for tissues or cell types using ENCODE data. Use when the user wants to characterize chromatin states, assemble histone modification panels, create epigenomic landscapes, run ChromHMM segmentation, identify super-enhancers or bivalent domains, profile regulatory elements across a biosample, or understand epigenetic regulation in a specific biological context. Covers histone marks, chromatin accessibility, TF binding, transcription, DNA methylation, and 3D genome structure.

日本語の概要は準備中です。原文の説明を表示しています。

Plan and execute integrative analysis combining multiple ENCODE experiments for cross-dataset or multi-omic workflows. Use when the user wants to combine experiments, perform cross-dataset comparison, multi-omic integration, peak overlap analysis, differential binding, signal correlation, chromatin state segmentation, enhancer-gene linkage, or any analysis that requires merging or comparing data from two or more ENCODE experiments. Covers same-assay cross-sample, multi-omic same-sample, cross-organism, and perturbation integration designs. Guides compatibility checks, batch effect detection, normalization, integration strategy selection, and provenance documentation.

日本語の概要は準備中です。原文の説明を表示しています。

Use when working on SAM 3 video segmentation, vaila_sam.py, checkpoint handling, or GPU memory issues.

日本語の概要は準備中です。原文の説明を表示しています。

Configure Communications Cloud for the first time: org setup sequence, permission sets, Enterprise Product Catalog (EPC) service catalog, TM Forum-aligned order decomposition setup, Account record-type segmentation, contract lifecycle activation. NOT for designing the commercial-to-technical order process itself - use admin/industries-process-design. NOT for calling TM Forum Open APIs (TMF622, TMF679) - use omnistudio/industries-api-extensions.

日本語の概要は準備中です。原文の説明を表示しています。

Use when designing nonprofit fundraising lifecycle stages, donor pipeline workflows, cultivation-to-stewardship cycles, or Salesforce Opportunity sales process configuration for NPSP or Nonprofit Cloud. Trigger keywords: fundraising lifecycle, donor pipeline, cultivation stage, solicitation workflow, major gift process, moves management, NPSP Opportunity stages, stewardship cycle, NPC fundraising stages. NOT for lapsed donor re-engagement or portfolio segmentation — use admin/donor-lifecycle-requirements. NOT for Engagement Plan setup — use admin/npsp-engagement-plans.

日本語の概要は準備中です。原文の説明を表示しています。

Requirements mapping for the full donor lifecycle in NPSP or Nonprofit Cloud: acquisition stage design, moves management, upgrade paths, lapsed donor re-engagement, and portfolio segmentation. NOT for mapping the Opportunity sales processes and stage picklists — use admin/fundraising-process-mapping. NOT for stewardship task automation — use admin/npsp-engagement-plans.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze nonprofit fundraising software for RFM donor segmentation, campaign performance modeling with A/B testing, recurring giving retention and failed payment recovery, major gift prospect scoring using capacity-affinity-propensity frameworks, event ROI calculation.

日本語の概要は準備中です。原文の説明を表示しています。