Googlielmo's blog

Content Based Image Retrieval (CBIR) systems are aimed to find similar images to an input image by querying an image data set. I am pretty sure you've used a CBIR several times before: here's the most popular one: The search in CBIRs isn't text-based as images are indexed by their visual content. Features are extracted from an image database and stored in some file system or object storage.Then, any time a new image is passed as search criterion, all those images which features are closest to the input image features are returned as results. The traditional feature extraction process relies on algorithms such as SURF or SIFT , but in this series I am going to describe my journey into CBIR using an unsupervised Deep Learning approach. Here's a preview of the first attempt, in order to search for food images (the input image in this case is an apple pie): In the next posts of this series I will walk through the details of the implementation before making thi...

During these strange days of emergency we could observe, among many others from the academy and the industry, lots of initiatives by individuals or groups of Data Scientists using public available data sets to make predictions about the evolution of the COVID-19 pandemic or other healthcare related applications to help in diagnosing the symptoms of the virus whether test kits for it wouldn't be available. Every little helps, it is also wonderful to see this high level of genuine interest on this matter and I am one of those that encourage people being curious and altruistic. But, as others have already started warning lately, any personal initiative, to be effective, needs to be evaluated by subject matter experts. In this post I am going to provide a concrete example about the importance of this kind of collaboration. At the end of 2019, I got a very bad flu which then ended up in an acute bronchitis, from which I recovered very slowly. During the rest of my life, after my ch...