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Found 24 papers, 4 papers with code
AdaCM$^2$: On Understanding Extremely Long-Term Video with Adaptive Cross-Modality Memory Reduction
The advancements in large language models (LLMs) have propelled the improvement of video understanding tasks by incorporating LLMs with visual models.
Beyond Point Annotation: A Weakly Supervised Network Guided by Multi-Level Labels Generated from Four-Point Annotation for Thyroid Nodule Segmentation in Ultrasound Image
Weakly-supervised methods typically guided the pixel-wise training by comparing the predictions to single-level labels containing diverse segmentation-related information at once, but struggled to represent delicate feature differences between nodule and background regions and confused incorrect information, resulting in underfitting or overfitting in the segmentation predictions.
S3Former: Self-supervised High-resolution Transformer for Solar PV Profiling
To meet this need, we introduce S3Former, designed to segment solar panels from aerial imagery and provide size and location information critical for analyzing the impact of such installations on the grid.
Practical considerations for variable screening in the Super Learner
However, the performance of a Super Learner using the lasso for dimension reduction has not been fully explored in cases where the lasso is known to perform poorly.
SolarFormer: Multi-scale Transformer for Solar PV Profiling
Accurate mapping of PV installations is crucial for understanding their adoption and informing energy policy.
On the robust learning mixtures of linear regressions
In this note, we consider the problem of robust learning mixtures of linear regressions.
SsciBERT: A Pre-trained Language Model for Social Science Texts
The academic literature of social sciences records human civilization and studies human social problems.
StyleBERT: Chinese pretraining by font style information
With the success of down streaming task using English pre-trained language model, the pre-trained Chinese language model is also necessary to get a better performance of Chinese NLP task.
Online Knowledge Distillation for Efficient Pose Estimation
However, existing pose distillation works rely on a heavy pre-trained estimator to perform knowledge transfer and require a complex two-stage learning procedure.
Effective Model Integration Algorithm for Improving Link and Sign Prediction in Complex Networks
Link and sign prediction in complex networks bring great help to decision-making and recommender systems, such as in predicting potential relationships or relative status levels.
Estimates of daily ground-level NO2 concentrations in China based on big data and machine learning approaches
We advanced a Random Forest model integrated K-means (RF-K) for the estimates with multi-source parameters.
Online Knowledge Distillation via Multi-branch Diversity Enhancement
Extensive experiments proved that our method significantly enhances the diversity among student models and brings better distillation performance.
More Information Supervised Probabilistic Deep Face Embedding Learning
Researches using margin based comparison loss demonstrate the effectiveness of penalizing the distance between face feature and their corresponding class centers.
Joint Deep Learning of Facial Expression Synthesis and Recognition
Firstly, a facial expression synthesis generative adversarial network (FESGAN) is pre-trained to generate facial images with different facial expressions.
Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing
Face anti-spoofing is crucial for the security of face recognition system, by avoiding invaded with presentation attack.
Multi-Level Network for High-Speed Multi-Person Pose Estimation
In multi-person pose estimation, the left/right joint type discrimination is always a hard problem because of the similar appearance.
Multi-Person Pose Estimation
Vocal Bursts Intensity Prediction
FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition
Human pose estimation has made significant advancement in recent years.
Selecting Biomarkers for building optimal treatment selection rules using Kernel Machines
Optimal biomarker combinations for treatment-selection can be derived by minimizing total burden to the population caused by the targeted disease and its treatment.
Optimization Design of Decentralized Control for Complex Decentralized Systems
A new method is developed to deal with the problem that a complex decentralized control system needs to keep centralized control performance.
IR2VI: Enhanced Night Environmental Perception by Unsupervised Thermal Image Translation
Context enhancement is critical for night vision (NV) applications, especially for the dark night situation without any artificial lights.
Efficient Correlated Topic Modeling with Topic Embedding
Correlated topic modeling has been limited to small model and problem sizes due to their high computational cost and poor scaling.
Revisiting Graph Construction for Fast Image Segmentation
In this paper, we propose a simple but effective method for fast image segmentation.
Text Network Exploration via Heterogeneous Web of Topics
A text network refers to a data type that each vertex is associated with a text document and the relationship between documents is represented by edges.
A Comparative Study of Object Trackers for Infrared Flying Bird Tracking
Bird strikes present a huge risk for aircraft, especially since traditional airport bird surveillance is mainly dependent on inefficient human observation.
