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In this paper, we introduce a novel approach using latent classifiers that can achieve comparable speed but better performance. The key idea is that instead of ...
Abstract—We study the problem of multi-class image classifica- tion with large number of classes, of which the one-vs-all based approach is prohibitive in ...
The research is focused on optimising two-layer perceptron for generalised scaled object classification problem. The optimisation criterion is minimisation ...
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Feb 8, 2023 · Large scale classification is achieved by subsampling both training data sets and classes in each output whereas downsized image input data is ...
Mar 21, 2024 · In this work, we introduce an alternative approach to detecting anomalies: using the penultimate layer of a neural network classifier as the latent space for ...
We propose a new learning algorithm of latent local support vector machines (SVM), called Latent-lSVM for effectively classifying very-high-dimensional, large- ...
Feb 12, 2023 · Extreme multilabel classification or XML, is an active area of interest in machine learning. Compared to traditional multilabel classification, ...
A MATLAB toolbox called Machine Learning in NeuroImaging (MALINI), which implements all the 18 different classifiers used for processing this data.
Feb 8, 2023 · Large scale classification is achieved by subsampling both training data sets and classes in each output whereas downsized image input data is ...
May 18, 2023 · I'm looking to construct a classification model, and I'm wondering if anyone has any advice for building a model with such high number of classes.
Missing: latent | Show results with:latent