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Use the consistent name "MILK10K Benchmark"
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stade/core/templates/base.html

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@@ -132,7 +132,7 @@ <h1><a href="{% url 'index' %}"><img src="{% static 'img/isic_logo.svg' %}"
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<div id="temporary-transition-banner" class="notification">
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<div class="container">
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<div class="notice-content">
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<h1 class="banner-title">The MILK10k Benchmarking Tool is open!</h1>
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<h1 class="banner-title">The MILK10k Benchmark is open!</h1>
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<h4 class="notice-title"><a href="{% url 'task-detail' 57 %}">Submit to the leaderboard!</a>!</h4>
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</div>
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</div>

stade/core/templates/landing/milk10k/index.html

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{% block content %}
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<section class="section container">
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<div class="section-header">
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<h1>{{ challenge.name }} Benchmarking Tool {% if challenge.locked %}[Closed]{% endif %}</h1>
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<h1>MILK10k Benchmark {% if challenge.locked %}[Closed]{% endif %}</h1>
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</div>
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<div class="section-content">
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<li>Metadata (more detail below)</li>
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</ul>
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<p>
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This benchmarking tool features the MILK10k training dataset (5,240 lesions) and a blind
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This benchmark features the MILK10k training dataset (5,240 lesions) and a blind
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held-out test dataset (479 lesions) called the MILK10k Benchmark.
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</p>
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</div>
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<div id="datasets">
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<h2>Datasets</h2>
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<p>
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This benchmarking tool features the MILK10k Benchmark dataset, comprising 958 images —
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This benchmark features the MILK10k Benchmark dataset, comprising 958 images —
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specifically, close-up and dermatoscopic image pairs for 479 skin lesions. The benchmark
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dataset originates from the same sources as the original
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<a href="https://doi.org/10.34970/262082">MILK10k</a> and covers the same eleven

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