<p>One architecture suited to your needs is <a href="https://en.wikipedia.org/wiki/WaveNet" rel="nofollow noreferrer">WaveNet</a>.</p>

<p>The WaveNet architecture is constructed to deal with very long sequences (your sequences are reasonably long) and has been shown to outperform LSTM based RNNs on several tasks in <a href="https://arxiv.org/pdf/1609.03499.pdf" rel="nofollow noreferrer">the original paper</a>.</p>

<p>I am not sure what you mean by</p>

<blockquote>
  <p>converting the above representations into an image and use CNNs to train</p>
</blockquote>

<p>so I would suggest sticking to recurrent models or WaveNet for sequence classification.</p>
Classifying Algorithm for time series data
<p>I have time series data(one instance of 30 seconds) as shown in the figure, I would like to know the what kind of classifying algorithms I could use.
<a href="https://i.stack.imgur.com/3Kja8.png" rel="nofollow noreferrer">This is how the data looks in time and frequency domain </a></p>

<p>In the image we have 2 classes(one represented in blue and the other in orange).On the left section of the image we have data represented in the time-domain and on the right its equivalent Fourier-Transform.
I am thinking of using LSTM to train the data for both domains and also converting the above representations into an image and use CNNs to train.
Any Suggestion such as a better algorithm or a better representation of data would help.</p>