Long-tailed classification
Web9 de abr. de 2024 · Propheter: Prophetic Teacher Guided Long-Tailed Distribution Learning. The problem of deep long-tailed learning, a prevalent challenge in the realm of generic visual recognition, persists in a multitude of real-world applications. To tackle the heavily-skewed dataset issue in long-tailed classification, prior efforts have sought to … Web14 de ago. de 2024 · Graphs in many domains follow a long-tailed distribution in their node degrees, i.e., a significant fraction of nodes are tail nodes with a small degree. Recent graph neural networks ... Kaihua Tang, Jianqiang Huang, and Hanwang Zhang. 2024 a. Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal …
Long-tailed classification
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Web1 de dez. de 2024 · Long-tailed distribution learning is a particular classification task in machine learning and has been widely studied [15], [18], [39]. For instance, Yang et al. [42] proposed a scalable algorithm based on image retrieval and superpixel matching for application to scene analysis, which employs tail classes to achieve a semantic … WebExisting long-tail image classification methods try to alleviate the head-tail imbalance majorly by re-balancing the data distribution, assigning the optimized weights, and augmenting information, but they often get in trouble with the trade-off on the head and tail performance which mainly caused by the poor representation learning of tail classes.
Web3 de out. de 2024 · For long-tailed classification, most works often pretrain a big model on a large-scale dataset, and then fine-tune the whole model for adapting to long-tailed … Web17 de ago. de 2024 · We codename the proposed method Long-tailed Object detector with Classification Equilibrium (LOCE). In summary, our contributions are as follows: (1) we propose to use the mean classification score to monitor the classification accuracy of each category during training; (2) we develop a score-guided equilibrium loss that …
Web16 de set. de 2024 · To accomplish this, we introduce a challenging new long-tailed chest X-ray benchmark to facilitate research on developing long-tailed learning methods for medical image classification. The benchmark consists of two chest X-ray datasets for 19- and 20-way thorax disease classification, containing classes with as many as 53,000 … WebAdversarial Robustness under Long-Tailed Distribution. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 8659--8668. Google Scholar …
Web24 de jun. de 2024 · Abstract: Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and accordingly unpromising …
WebSpecifically, our theory shows that the SGD momentum is essentially a confounder in long-tailed classification. On one hand, it has a harmful causal effect that misleads the tail prediction biased towards the head. On the other hand, its induced mediation also benefits the representation learning and head prediction. Our framework elegantly ... list of unsdgsWeb28 de set. de 2024 · Therefore, long-tailed classification is the key to deep learning at scale. However, existing methods are mainly based on re-weighting/re-sampling … list of unus annus videos by dateWebFor natural language processing (NLP) ‘text-to-text’ tasks, prevailing approaches heavily rely on pretraining large self-supervised models on massive external datasources. However, this methodology is being critiqued for: exceptional compute and pretraining data requirements; diminishing returns on both large and small datasets; and importantly, favourable … list of upcoming animated disney moviesWeb27 de fev. de 2024 · Request PDF Long-Tailed Classification with Gradual Balanced Loss and Adaptive Feature Generation The real-world data distribution is essentially long-tailed, which poses great challenge to ... list of upbeat dance songsWeb1 de dez. de 2024 · Long-tailed distribution learning is a particular classification task in machine learning and has been widely studied [15], [18], [39]. For instance, Yang et al. [42] proposed a scalable algorithm based on image retrieval and superpixel matching for application to scene analysis, which employs tail classes to achieve a semantic … list of upcoming barbie moviesWeb1 de nov. de 2024 · Especially for long-tailed CIFAR-100-LT with an imbalanced ratio of 200 (an extreme imbalance case), our model achieves 40.64% classification accuracy, which is 1.95% better than LDAM-DCB. Similarly, our model achieves 30.1% classification accuracy, which is 2.32% better than the optimal method for long-tailed the Tiny … immortals fenyx rising shrine of aitherWebExisting long-tailed classification (LT) methods only focus on tackling the class-wise imbalance that head classes have more samples than tail classes, but overlook the attribute-wise imbalance.In fact, even if the class is balanced, samples within each class may still be long-tailed due to the varying attributes. immortals fenyx rising secret trial