TASK DEFINITION: In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].
PROBLEM: This is an interesting article, present develop of a mobile robot use as beach cleaner. I have 2 comments about the design, I think will be interesting define what is the dimension of collector and storage compartment for know what is the capacity of this cleaner. In page 2 in the first paragraph a typo mistake was found.

SOLUTION: en

PROBLEM: This is an interesting paper about quantized networks that work on temporal difference inputs. The basic idea is that when a network has only to process differences then this is computational much more efficient specifically with natural video data since large parts of an image would be fairly constant so that the network only has to process the informative sections of the image (video stream). This is of course how the human visual system works, and it is hence of interest even beyond the core machine learning community. As an aside, there is a strong community interested in event-based vision such as the group of Tobi Delbruck, and it might be interesting to connect to this community. This might even provide a reference for your comments on page 1. I guess the biggest novel contribution is that a rounding network can be replaced by a sigma-delta network, but that the order of discretization and summation doe make some difference in the actual processing load. I think I followed the steps and Most of my questions have already been answers in the pre-review period. My only question remaining is on page 3, "It should be noted that when we refer to "temporal differences", we refer not to the change in the signal over time, but in the change between two inputs presented sequentially. The output of our network only depends on the value and order of inputs, not on the temporal spacing between them." This does not make sense to me. As I understand you just take the difference between two frames regardless if you call this temporal or not it is a change in one frame. So this statement rather confuses me and maybe should be dropped unless I do miss something here, in which case some more explanation would be necessary. Figure 1 should be made bigger. An improvement of the paper that I could think about is a better discussion of the relevance of the findings. Yes, you do show that your sigma-delta network save some operation compared to threshold, but is this difference essential for a specific task, or does your solution has relevance for neuroscience?

SOLUTION: en

PROBLEM: El paper muestra una aplicacion practica desarrollada con realidad aumentada aplicada a entregar informacion turistica en espacios abiertos El trabajo permitira dar a conocer la tecnologia a nivel nacional y sus potencialidades, por lo que se considera un aporte. Sin embargo, el paper carece de un estudio comparativo con otros trabajos similares aplicando esta tecnologia a este mismo objetivo, por lo que no se logra obtener una idea del grado de originalidad del mismo, ni da la posibilidad de contrastar algunas de las limitaciones del mismo que el autor menciona al final del paper con trabajos ya desarrollados anteriormente.

SOLUTION:
es