
AI AdBlocker wot eye3
AI-powered blocker (your path) Hybrid rules + on-page heuristic for Firefox MV2. Uses a machine learning model (running in the browser with ONNX Runtime) to see or analyze the DOM.
Někotre funkcije móhli sej płaćenje wužadaćNěkotre funkcije móhli sej płaćenje wužadać
Za Firefox za Android™ k dispozicijiZa Firefox za Android™ k dispoziciji
1 wužiwar1 wužiwar
Trjebaće Firefox, zo byšće tute rozšěrjenje wužiwał
Metadaty rozšěrjenja
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Wo tutym rozšěrjenju
This add-on is a starter AI Ad Block extension.
• The uploaded .zip is the Firefox-compatible build (no rules/ directory, uses background.scripts instead of service_worker).
• The uploaded source .zip contains the full, human-readable source code (TypeScript, scripts, manifests, build files) without dist/ or node_modules/.
• No remote code execution, dynamic code generation, or obfuscated code is used.
• Can detect hidden ads, sponsored labels, promoted posts, native ads that rule-based systems miss.
• Can adapt better if you re-train the model with new data.
Example AI Features You Can Add DOM / Heuristic Classifier:
Train a lightweight ML model on HTML snippets (features: tag type, attributes, text like “Sponsored”).
Content script grabs candidate nodes → runs model → hide if classified as ad.
Vision-based Ad Detection:
Use a small CNN (e.g., MobileNet/ONNX quantized) to check if an <img> looks like a banner ad.
Useful for “image-only” ads where markup doesn’t give them away.
Hybrid (most practical):
Use heuristics to filter likely candidates (divs with fixed size, suspicious classes, “sponsored” text).
Use ML to confirm → avoid false positives.
Future-proofing: when advertisers obfuscate HTML/CSS, rules break → but your ML model still generalizes.
Privacy-preserving: everything runs locally in the browser; no need to send page data to servers.
Research value: positions your extension as “next-gen” ad blocker, different from commodity ones.
• The uploaded .zip is the Firefox-compatible build (no rules/ directory, uses background.scripts instead of service_worker).
• The uploaded source .zip contains the full, human-readable source code (TypeScript, scripts, manifests, build files) without dist/ or node_modules/.
• No remote code execution, dynamic code generation, or obfuscated code is used.
• Can detect hidden ads, sponsored labels, promoted posts, native ads that rule-based systems miss.
• Can adapt better if you re-train the model with new data.
Example AI Features You Can Add DOM / Heuristic Classifier:
Train a lightweight ML model on HTML snippets (features: tag type, attributes, text like “Sponsored”).
Content script grabs candidate nodes → runs model → hide if classified as ad.
Vision-based Ad Detection:
Use a small CNN (e.g., MobileNet/ONNX quantized) to check if an <img> looks like a banner ad.
Useful for “image-only” ads where markup doesn’t give them away.
Hybrid (most practical):
Use heuristics to filter likely candidates (divs with fixed size, suspicious classes, “sponsored” text).
Use ML to confirm → avoid false positives.
Future-proofing: when advertisers obfuscate HTML/CSS, rules break → but your ML model still generalizes.
Privacy-preserving: everything runs locally in the browser; no need to send page data to servers.
Research value: positions your extension as “next-gen” ad blocker, different from commodity ones.
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Prawa a datyDalše informacije
Trěbne prawa:
- Přistup k wašim datam za wšě websydła měć
Dalše informacije
- Přidatkowe wotkazy
- Wersija
- 0.1.0
- Wulkosć
- 2,89 MB
- Posledni raz zaktualizowany
- pred 6 dňami (18. aug 2025)
- Přiwuzne kategorije
- Licenca
- Licenca MIT
- Prawidła priwatnosće
- Čitajće prawidła priwatnosće za tutón přidatk
- Wersijowa historija
- Zběrce přidać
Tutoho wuwiwarja podpěrać
Wuwiwar tutoho rozšěrjenja was prosy, mały přinošk darić, zo byšće jeho wuwiće podpěrał.
Wjace rozšěrjenjow wot eye3
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It does not collect or transmit user data.
Reviewers can build the extension from source using the included scripts (see README).