Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Cogni-Net: Cognitive Feature Learning through Deep Visual Perception   Can we ask computers to recognize what we see from brain signals alone? Our
paper seeks to utilize the knowledge learnt in the visual domain by popular
pre-trained vision models and use it to teach a recurrent model being trained
on brain signals to learn a discriminative manifold of the human brain's
cognition of different visual object categories in response to perceived visual
cues. For this we make use of brain EEG signals triggered from visual stimuli
like images and leverage the natural synchronization between images and their
corresponding brain signals to learn a novel representation of the cognitive
feature space. The concept of knowledge distillation has been used here for
training the deep cognition model, CogniNet\footnote{The source code of the
proposed system is publicly available at
{https://www.github.com/53X/CogniNET}}, by employing a student-teacher learning
technique in order to bridge the process of inter-modal knowledge transfer. The
proposed novel architecture obtains state-of-the-art results, significantly
surpassing other existing models. The experiments performed by us also suggest
that if visual stimuli information like brain EEG signals can be gathered on a
large scale, then that would help to obtain a better understanding of the
largely unexplored domain of human brain cognition.

2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph