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0:41
YouTube
NextGen AI Explorer
Custom Loss Function #3: Contrastive Loss for Similarity Learning #ai #artificialintelligence Custom
For tasks involving similarity learning, such as face verification or signature verification, Contrastive Loss is a powerful ally. This loss function aims to bring similar data points closer while pushing dissimilar ones apart, thus learning a feature space where similarity is meaningful. By focusing on pairs of samples, Contrastive Loss ...
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AI • Machine Learning • Tech on Instagram: "SimCLR (Simple Contrastive Learning of Representations) is a technique for self-supervised learning, primarily designed to learn representations from unlabeled data. The main idea behind SimCLR is to use contrastive learning to map similar data points closer together in the representation space while pushing dissimilar ones apart. This is achieved by creating augmented views of the same image and training a neural network to recognize that these augmen
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