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Found 8 papers, 3 papers with code
TikTokActions: A TikTok-Derived Video Dataset for Human Action Recognition
We find that the performance of the model pre-trained using our Tik-Tok dataset is comparable to models trained on larger action recognition datasets (95. 3% on UCF101 and 53. 24% on HMDB51).
Multimodal deep representation learning for quantum cross-platform verification
Cross-platform verification, a critical undertaking in the realm of early-stage quantum computing, endeavors to characterize the similarity of two imperfect quantum devices executing identical algorithms, utilizing minimal measurements.
Computer Vision Estimation of Emotion Reaction Intensity in the Wild
Emotions play an essential role in human communication.
Shuffle-QUDIO: accelerate distributed VQE with trainability enhancement and measurement reduction
To gain such computational advantages on large-scale problems, a feasible solution is the QUantum DIstributed Optimization (QUDIO) scheme, which partitions the original problem into $K$ subproblems and allocates them to $K$ quantum machines followed by the parallel optimization.
PoseFace: Pose-Invariant Features and Pose-Adaptive Loss for Face Recognition
Despite the great success achieved by deep learning methods in face recognition, severe performance drops are observed for large pose variations in unconstrained environments (e. g., in cases of surveillance and photo-tagging).
Accelerating variational quantum algorithms with multiple quantum processors
Variational quantum algorithms (VQAs) have the potential of utilizing near-term quantum machines to gain certain computational advantages over classical methods.
The dilemma of quantum neural networks
The core of quantum machine learning is to devise quantum models with good trainability and low generalization error bound than their classical counterparts to ensure better reliability and interpretability.
TopicModel4J: A Java Package for Topic Models
Topic models provide a flexible and principled framework for exploring hidden structure in high-dimensional co-occurrence data and are commonly used natural language processing (NLP) of text.
