The article presents a comprehensive benchmarking of different selective classification frameworks that are based on deep neural networks. Selective classification allows a model to abstain from making a prediction when…
Continue readingThe paper proposes two novel models: DI-AEC and FADI-AEC for Acoustic Echo Cancellation (AEC). These models pioneer a diffusion-based stochastic regeneration approach for AEC, with FADI-AEC designed to save computational…
Continue readingThis article presents MAMI, a method to improve long sequence neuron captioning. Neuron labeling is a way to visualize how neurons in a deep neural network respond to certain patterns….
Continue readingThe article explores a method for early detection of breast cancer using mammography in a realistic hospital setting. It challenges the constraints of existing methods, which require annotations for individual…
Continue readingLightGlue is a deep learning model designed to match local features across images. It improves upon SuperGlue, the current state-of-the-art in sparse matching, by offering more efficient memory and computation…
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