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added new bkgnd image
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@TTAyanlade
TTAyanlade committed Apr 29, 2024
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8 changes: 5 additions & 3 deletions css/styles.css
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Expand Up @@ -521,7 +521,7 @@ input[type='checkbox'] {
.header {
padding-top: 7rem;
padding-bottom: 5.5rem;
background: linear-gradient(rgba(0, 0, 0, 0.5), rgba(0, 0, 0, 0.3)), url('../images/header-background.jpg') center center no-repeat;
background: linear-gradient(rgba(0, 0, 0, 0.5), rgba(0, 0, 0, 0.3)), url('../images/mlcas_bg_all.png') center center no-repeat;
background-size: cover;
text-align: center;
}
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/* Header */
.header {
padding-top: 11rem;
padding-bottom: 9rem;
/* padding-top: 11rem;
padding-bottom: 9rem; */
padding-top: 7rem;
padding-bottom: 5rem;
}
/* end of header */

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Binary file added images/mlcas_bg_all.png
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40 changes: 19 additions & 21 deletions index.html
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<div class="col-lg-10">
<div class="text-container">
<h3 class="h1-large">Sixth International Workshop on Machine Learning for Cyber-Agricultural
Systems <br>(MLCAS2024)</h3>
Systems <br>(MLCAS2024)</h3>
<!-- <h5 class="text-warning">Step 1: Register</h5><a class="btn-solid-lg page-scroll" href="https://forms.gle/CM497FP3jGVY2JRb8" target="_blank">Pre-Registration</a> TOBEDONE-->
<h5 class="text-warning">Step 1: Register</h5><a class="btn-solid-lg page-scroll" href="" target="_blank">Pre-Registration Opens Soon</a>
</div> <!-- end of text-container -->
Expand Down Expand Up @@ -138,27 +138,25 @@ <h5 class="text-warning mt-3">Step 2: Payment <span class="text-white">(Please u
<div class="container">
<div class="row">
<div class="col-xl-10 offset-xl-1">
<h5 class="text-center text-muted mt-2">Previous MLCAS workshops: <a href="https://2023.mlcas.site/" target="_blank">MLCAS2022</a>; <a href="https://mlcas2022.github.io/" target="_blank">MLCAS2021</a></h5>
<h5 class="text-center text-muted mt-2">Previous MLCAS workshops: <a href="https://2023.mlcas.site/" target="_blank">MLCAS2023</a>; <a href="https://mlcas2022.github.io/" target="_blank">MLCAS2022</a></h5>

<h5 class="text-center text-muted mt-2">This workshop is supported by NSF (U.S.A), USDA-NIFA (U.S.A), and JST (Japan)</h5>

<p class="mt-2">Today, efficient and cost-effective sensors as well as high performance
computing technologies are looking to transform traditional plant-based agriculture into an
efficient cyber-physical system. The easy availability of cheap, deployable, connected
sensor technology has created an enormous opportunity to collect vast amount of data at
varying spatial and temporal scales at both experimental and production agriculture levels.
Therefore, both offline and real-time agricultural analytics that assimilates such
heterogeneous data and provides automated, actionable information is a critical needed for
sustainable and profitable agriculture.</p>
<p class="mb-3">Data analytics and decision-making for Agriculture has been a
long-standing application area. The application of advanced machine learning methods to this
critical societal need can be viewed as a transformative extension for the agriculture
community. In this workshop, we intend to bring together academic and industrial researchers
and practitioners in the fields of machine learning, data science and engineering, plant
sciences and agriculture, in the collaborative effort of identifying and discussing major
technical challenges and recent results related to machine learning-based approaches. It
will feature invited talks, oral/poster presentation of accepted papers, and a panel
discussion. </p>
<p class="mt-2">Today, efficient, cost-effective sensors as well as high performance computing technologies
are looking to transform traditional plant-based agriculture into an efficient cyber-physical system. The
easy availability of cheap, deployable, connected sensor technology has created an enormous opportunity to
collect vast amounts of data at varying spatial and temporal scales at both experimental and production
agriculture levels. Therefore, both offline and real-time agricultural analytics that assimilates such
heterogeneous data and provides automated, actionable information is a critical need for sustainable and
profitable agriculture.</p>
<p class="mb-3">Data analytics and decision-making for Agriculture has been a long-standing application area.
The application of advanced Artificial Intelligence (AI) and Machine Learning (ML) methods to this critical
societal need can be viewed as a transformative extension for the agriculture community. In this workshop,
we intend to bring together academic and industrial researchers and practitioners in the fields of machine
learning, data science and engineering, plant sciences and agriculture, in the collaborative effort of
identifying and discussing major technical challenges and recent results related to machine learning-based
approaches. It will feature invited talks, oral/poster presentations of accepted papers, and an Ag-ML
competition. </p>

<ul class="list-unstyled li-space-lg mb-3">
<li class="media">
Expand All @@ -184,8 +182,8 @@ <h5 class="text-center text-muted mt-2">This workshop is supported by NSF (U.S.A
<h5 class="text-center text-warning mt-3"> Gold Sponsors</h5>
<div class="icons-container">
<div class="d-flex justify-content-center">
<img src="https://mlcas2022.github.io/images/jd_logo.png" alt="John Deere Logo" height="100px" class="m-2" onclick="javascript:window.open('https://www.deere.com/en/', '_blank');">
<img src="https://mlcas2022.github.io/images/bayer_logo.svg" alt="Bayer Logo" height="100px" class="m-2" onclick="javascript:window.open('https://www.bayer.com/en/', '_blank');">
<img src="images/jd_logo.png" alt="John Deere Logo" height="100px" class="m-2" onclick="javascript:window.open('https://www.deere.com/en/', '_blank');">
<img src="images/bayer_logo.svg" alt="Bayer Logo" height="100px" class="m-2" onclick="javascript:window.open('https://www.bayer.com/en/', '_blank');">
</div>
</div>
</div>
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