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Found 8 papers, 2 papers with code
Data Efficient Training with Imbalanced Label Sample Distribution for Fashion Detection
Multi-label classification models have a wide range of applications in E-commerce, including visual-based label predictions and language-based sentiment classifications.
HalluAudio: Hallucinating Frequency as Concepts for Few-Shot Audio Classification
Few-shot audio classification is an emerging topic that attracts more and more attention from the research community.
FedRule: Federated Rule Recommendation System with Graph Neural Networks
Much of the value that IoT (Internet-of-Things) devices bring to ``smart'' homes lies in their ability to automatically trigger other devices' actions: for example, a smart camera triggering a smart lock to unlock a door.
Package Theft Detection from Smart Home Security Cameras
Package theft detection has been a challenging task mainly due to lack of training data and a wide variety of package theft cases in reality.
Adaptive Distillation: Aggregating Knowledge from Multiple Paths for Efficient Distillation
Despite this advancement in different techniques for distilling the knowledge, the aggregation of different paths for distillation has not been studied comprehensively.
Ranked #33 on
Knowledge Distillation
on ImageNet
TransMatch: A Transfer-Learning Scheme for Semi-Supervised Few-Shot Learning
Under the proposed framework, we develop a novel method for semi-supervised few-shot learning called TransMatch by instantiating the three components with Imprinting and MixMatch.
Open-Ended Visual Question Answering by Multi-Modal Domain Adaptation
A straightforward solution is to fine-tune a pre-trained source model by using those limited labeled target data, but it usually cannot work well due to the considerable difference between the data distributions of the source and target domains.
AI for Earth: Rainforest Conservation by Acoustic Surveillance
Saving rainforests is a key to halting adverse climate changes.
BIG-bench Machine Learning
Environmental Sound Classification
+2
