Specificity
348 papers with code • 0 benchmarks • 1 datasets
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MACSum
Most implemented papers
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
alexander-rakhlin/ICIAR2018
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In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification.
OPIEC: An Open Information Extraction Corpus
In this paper, we release, describe, and analyze an OIE corpus called OPIEC, which was extracted from the text of English Wikipedia.
Use What You Have: Video Retrieval Using Representations From Collaborative Experts
albanie/collaborative-experts
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The rapid growth of video on the internet has made searching for video content using natural language queries a significant challenge.
Grounding Representation Similarity with Statistical Testing
To understand neural network behavior, recent works quantitatively compare different networks' learned representations using canonical correlation analysis (CCA), centered kernel alignment (CKA), and other dissimilarity measures.
Specificity-preserving RGB-D Saliency Detection
To effectively fuse cross-modal features in the shared learning network, we propose a cross-enhanced integration module (CIM) and then propagate the fused feature to the next layer for integrating cross-level information.
How Do Vision Transformers Work?
xxxnell/how-do-vits-work
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ICLR 2022
In particular, we demonstrate the following properties of MSAs and Vision Transformers (ViTs): (1) MSAs improve not only accuracy but also generalization by flattening the loss landscapes.
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets
Deep generative models have achieved tremendous success in designing novel drug molecules in recent years.
Rotation Invariant Transformer for Recognizing Object in UAVs
whucsy/rottrans
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ACM Multimedia 2022
Existing methods are usually designed for city cameras, incapable of handing the rotation issue in UAV scenarios.
Cross-Lingual Adaptation using Structural Correspondence Learning
From these correspondences a cross-lingual representation is created that enables the transfer of classification knowledge from the source to the target language.
Deep Region and Multi-Label Learning for Facial Action Unit Detection
Region learning (RL) and multi-label learning (ML) have recently attracted increasing attentions in the field of facial Action Unit (AU) detection.
