Identifying Blue Whales Using a Computer Vision Approach
CRIM’s computer vision team is called upon to solve all kinds of image or video analysis problems related to fields as varied as industrial inspection, dermatology, microscopic imaging, 3D imaging , etc.
From PyTorch to Libtorch: tips and tricks
Deep learning practitioners hone their skills using PyTorch and Python as their tools of choice. For that reason, on-line courses, blog posts, tutorials, etc. introducing PyTorch to new users abound on the internet. That is not the case for Libtorch, PyTorch’s C++ API, which lags behind in terms of user base size despite the fact […]
Contributing to LibTorch: recent architectures and “vanilla” training pipeline
In August 2021, a PR aimed at adding a SOTA architecture (namely EfficientNet) to TorchVision, a Python-based PyTorch package for computer vision experiments, was submitted on GitHub. Even though deep learning practitioners are used to testing new architectures that are regularly posted on this platform, this is certainly a welcome contribution. On the other hand, C++ contributions […]
Deep learning applied to graphs: Extraction and processing of graph information by convolutional neural networks
Graphs — frequently used in the fields of transport, telecommunication, biology, sociology and others — allow, in the simplest cases, an exploration of data and their connectivity from a simple visual analysis. However, in most applications, for example in the classic case of the representation of social networks, the graphs obtained contain an immense quantity […]