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Found 7 papers, 3 papers with code
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions
EX2 uses reinforcement learning to align a large language model with VLM preferences and generates descriptions that incorporate the important features for the VLM.
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
However, current zero-shot methods select a subset of attributes regardless of commonalities between the target classes, potentially providing no useful information that would have helped to distinguish between them.
An Adaptive Method for Weak Supervision with Drifting Data
In particular, at each step, our algorithm guarantees an estimation of the current accuracies of the weak supervision sources over a window of past observations that minimizes a trade-off between the error due to the variance of the estimation and the error due to the drift.
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
In many practical few-shot learning problems, even though labeled examples are scarce, there are abundant auxiliary datasets that potentially contain useful information.
Multiple Abnormality Detection for Automatic Medical Image Diagnosis Using Bifurcated Convolutional Neural Network
In recent years portable medical imaging devices such as capsule endoscopy and digital dermatoscope have been introduced and made the diagnosis procedure easier and more efficient.
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames
Both CNN and MLP structures are simplified to reduce the number of computational operations.
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders.
