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Tropical forest conservation is a current issue of social and ecological relevance, due to their important role in the global ecosystem. Tropical forests have a great diversity of fauna and flora, act in the regulation of climate and rainfall, absorb large amounts of carbon dioxide, and serve as a home for countless indigenous peoples. Unfortunately, for years, thousands of hectares have been deforested and degraded in the Amazon rainforest. Government programs and private initiatives have emerged with the aim of mitigating the effects of the caused damage through monitoring and inspection. Most monitoring programs involve the inspection of remote sensing images by specialists, generally counting on the support of computational resources for automatic detection of patterns. This thesis proposes a novel %deforestation detection system called ForestEyes, which aims to detect deforestation in tropical forests based on Citizen Science and Machine Learning approaches. ForestEyes project uses non-specialist volu...

In this paper, entitled "The Good, the Bad, and the Ugly: Neural Networks Straight from JPEG", we investigate whether the spatial resolution and JPEG quality affects the performance of CNNs fed with DCT coefficients. More specifically, we studied several aspects of a state-of-the-art CNN recently proposed by Gueguen et al. [1], which is a modified version of the ResNet-50 architecture [2]. Despite the speed-up obtained by partially decoding JPEG images, their architectural changes raised the computation complexity and the number of parameters of the network. To alleviate these drawbacks, we propose a Frequency Band Selection (FBS) technique to select the most relevant DCT coefficients before feeding them to the network. A comparison among the original ResNet-50 network [2], the modified ResNet-50 network proposed by Gueguen et al. [1], and our improved version with FBS is presented below. Original ResNet-50 network [2] ResNet-50 using DCT as input [1]...

Today was held a presentation of the GIBIS in the context of the Academic Orientation Week. Two sessions were organized: the first, from 17:15 to 18:30; and second, from 21:45 to 22:30. They were attended by the professors Jurandy Almeida, Fabio Faria and Claudio Shida, and by the students Lucas Lellis, Anderson Faria and Leonardo Duarte. We extend a warm thank you to everyone who was present to know a little bit about our work.