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Found 6 papers, 1 papers with code
Contrastive Learning and Cycle Consistency-based Transductive Transfer Learning for Target Annotation
The transductive transfer learning (TTL) method that incorporates a CycleGAN-based unpaired domain translation network has been previously proposed in the literature for effective ATR annotation.
Text-Guided Face Recognition using Multi-Granularity Cross-Modal Contrastive Learning
However, learning a discriminative joint embedding within the multimodal space poses a considerable challenge due to the semantic gap in the unaligned image-text representations, along with the complexities arising from ambiguous and incoherent textual descriptions of the face.
Improving Face Recognition from Caption Supervision with Multi-Granular Contextual Feature Aggregation
Additionally, we design a textual feature refinement module (TFRM) that refines the textual features of the pre-trained BERT encoder by updating the contextual embeddings.
Word level Bangla Sign Language Dataset for Continuous BSL Recognition
The proposed model utilizes human pose information, which has shown to be successful in analyzing sign language patterns.
Deep Learning based Early Detection and Grading of Diabetic Retinopathy Using Retinal Fundus Images
Diabetic Retinopathy (DR) is a constantly deteriorating disease, being one of the leading causes of vision impairment and blindness.
DEEPGONET: Multi-label Prediction of GO Annotation for Protein from Sequence Using Cascaded Convolutional and Recurrent Network
The present gap between the amount of available protein sequence due to the development of next generation sequencing technology (NGS) and slow and expensive experimental extraction of useful information like annotation of protein sequence in different functional aspects, is ever widening, which can be reduced by employing automatic function prediction (AFP) approaches.
