Viso.ai

JANUARY 16, 2024

Matching Networks: The algorithm computes embeddings using a support set, and one-shot learns by classifying the query data sample based on which support set embedding is closest to the query embedding – source. The embedding functions can be convolutional neural networks (CNNs). The CLIP model for ZSL shows 64.3%

Neural Network 52

Neural Network Computer Vision Convolutional Neural Networks Algorithm 52

Unite.AI

OCTOBER 10, 2024

Source: [link] ‘This phenomenon,' they explain, ‘termed “compression helps” in the [2021] paper, is justified by the fact that compression can remove noise and disturbing background features, thereby highlighting the main object in an image, which helps DNNs make better prediction.'

Neural Network 162

Neural Network Convolutional Neural Networks Deep Learning Explainability 162

ML Review

MAY 3, 2018

Source : Hassanat (2011) [13] These approaches obtained impressive results (over 70% word accuracy) for tests performed with classifiers trained on the same speaker they were tested on. One can also think of CTC as similar to a softmax due to converting the raw output of a network (e.g. Online] arXiv: 1710.01288. Hassanat, A.B.A.

Neural Network 52

Neural Network Computer Vision Deep Learning Convolutional Neural Networks 52