Automated Artemia Detection and Length Measurement Using Deep Convolutional Networks

This thesis studies empirical properties of deep convolutional neural net- works, and in particular the Scattering Transform.. Indeed, the theoretical anal- ysis of the latter is

To conclude, the recent reviews of French Artemia populations observed during the 1800s and located along the Atlantic and Mediterranean coasts showed that: i) two out the four

For the Text-Based Fake News Detection subtask, we proposed a neural network that combines textual features encoded by a pre-trained BERT model and metadata of tweets encoded by

Multistep classification methods using a shallow classifier trained on features extracted from a neural network, outper- formed the base neural network when tested on noisy data and

A global averaging pooling (GAP) layer is used to connect the last convolutional layer and the output layer. As data augmentation, image transformations are used

The long- term consequence of sexual conflicts can be studied ex- perimentally in the laboratory on model organisms such as Drosophila (Arnqvist & Rowe, 2005). They

The success of explicit position and scale search in image classification suggests using DCNNs for sliding- window detection; even though for pedestrians excellent re- sults have

This strategy is much harder and not feasible for common objects as they are a lot more diverse. As an illustration, the winner of the COCO challenge 2017 [274], which used many of