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GitHub - seanoliver/audioflare: An all-in-one AI audio playground using Cloudflare AI Workers to transcribe, analyze, summarize, and translate any audio file.

An all-in-one AI audio playground using Cloudflare AI Workers to transcribe, analyze, summarize, and translate any audio file. - GitHub - seanoliver/audioflare: An all-in-one AI audio playground using Cloudflare AI Workers to transcribe, analyze, summarize, and translate any audio file.
Report Bug Text Classification Image Classification Text Embedding Feature Branch
Source: github.com

"LibFewShot: A Comprehensive Library for Few-Shot Learning" by Wenbin Li, Ziyi Wang et al.

Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly show that many generic techniques or “tricks”, such as data augmentation, pre-training, knowledge distillation, and self-supervision, may greatly boost the performance of a few-shot learning method. Moreover, different works may employ different software platforms, backbone architectures and input image sizes, making...
Benchmark Testing Deep Learning Hair Comparison Few Shot Learning Image Classification Task Analysis
Source: uow.edu.au

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"Going Deeper with Recursive Convolutional Layers" by Johan Chagnon, Markus Hagenbuchner et al.

The development of Convolutional Neural Networks (CNNs) trends towards models with an ever growing number of Convolutional Layers (CLs) and increases the number of trainable parameters significantly. Such models are sensitive to these structural parameters, which implies that large models have to be carefully tuned using hyperparameter optimisation, a process that can be very time consuming. In this paper, we study the usage of Recursive Convolutional Layers (RCLs), a module relying on an algebr...
Convolutional Neural Networks Cnns Convolutional Neural Networks Convolutional Layers Recursive Convolutional Layers Convolutional Neural Network Dynamic Depth
Source: uow.edu.au

GitHub - vaynexie/CWOX: A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.

A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification. - GitHub - vaynexie/CWOX: A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.
Hong Kong Weiyan Xie Hong Kong University Of Science Two Stage Contrastive Whole Output Explanation Image Classification Label Confusion Clusters
Source: github.com

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