Search Results for author:
Found 7 papers, 6 papers with code
Data-Efficient Unsupervised Interpolation Without Any Intermediate Frame for 4D Medical Images
4D medical images, which represent 3D images with temporal information, are crucial in clinical practice for capturing dynamic changes and monitoring long-term disease progression.
ProxyDet: Synthesizing Proxy Novel Classes via Classwise Mixup for Open-Vocabulary Object Detection
Open-vocabulary object detection (OVOD) aims to recognize novel objects whose categories are not included in the training set.
GeNAS: Neural Architecture Search with Better Generalization
Recent neural architecture search (NAS) approaches rely on validation loss or accuracy to find the superior network for the target data.
Distilling Linguistic Context for Language Model Compression
A computationally expensive and memory intensive neural network lies behind the recent success of language representation learning.
Contextual Knowledge Distillation for Transformer Compression
A computationally expensive and memory intensive neural network lies behind the recent success of language representation learning.
Attribution Preservation in Network Compression for Reliable Network Interpretation
Neural networks embedded in safety-sensitive applications such as self-driving cars and wearable health monitors rely on two important techniques: input attribution for hindsight analysis and network compression to reduce its size for edge-computing.
MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding
Thus, in addition to the joint embedding space, we propose a novel multi-head self-attention network to capture various components of visual and textual data by attending to important parts in data.
