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Found 11 papers, 3 papers with code
Gaussian-smoothed Imbalance Data Improves Speech Emotion Recognition
We find the data distribution in the IEMOCAP dataset is very imbalanced, which may harm models to learn a better representation.
Bidirectional Semi-supervised Dual-branch CNN for Robust 3D Reconstruction of Stereo Endoscopic Images via Adaptive Cross and Parallel Supervisions
The learned knowledge flows across branches along two directions: a cross direction (disparity guides distribution in ACS) and a parallel direction (disparity guides disparity in APS).
Sequence-to-Set Generative Models
We present GRU2Set, which is an instance of our sequence-to-set method and employs the famous GRU model as the sequence generative model.
Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspective
Knowledge graph completion (KGC) aims to infer missing knowledge triples based on known facts in a knowledge graph.
Tripartite: Tackle Noisy Labels by a More Precise Partition
Instead, we propose a Tripartite solution to partition training data more precisely into three subsets: hard, noisy, and clean.
PP-ShiTu: A Practical Lightweight Image Recognition System
In recent years, image recognition applications have developed rapidly.
Automatic Identification of the End-Diastolic and End-Systolic Cardiac Frames from Invasive Coronary Angiography Videos
More specifically, a detection algorithm is first used to detect the key points of coronary arteries, and then an optical flow method is employed to track the trajectories of the selected key points.
PP-LCNet: A Lightweight CPU Convolutional Neural Network
We propose a lightweight CPU network based on the MKLDNN acceleration strategy, named PP-LCNet, which improves the performance of lightweight models on multiple tasks.
Multi-Classifier Interactive Learning for Ambiguous Speech Emotion Recognition
In recent years, speech emotion recognition technology is of great significance in industrial applications such as call centers, social robots and health care.
The Promises of Parallel Outcomes
In contrast to existing proposals in the literature, the roles of multiple outcomes in our key identification assumption are symmetric, hence the name parallel outcomes.
Causal Inference
Methodology
Range-Doppler Information and Doppler Scattering Information in Multipulse Radar
In this paper, the general radar measurement probfilems of determining range, Doppler frequency and scatteringproperties parameters are investigated from the viewpoint of Shannons information theory.
