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Found 16 papers, 2 papers with code
Modeling Hierarchical Structural Distance for Unsupervised Domain Adaptation
Compared with the ground distance of the conventional domain-level OT, the image-level OT captures structural associations among local regions of images that are beneficial to classification.
Duck swarm algorithm: theory, numerical optimization, and applications
A swarm intelligence-based optimization algorithm, named Duck Swarm Algorithm (DSA), is proposed in this study, which is inspired by the searching for food sources and foraging behaviors of the duck swarm.
Speech-T: Transducer for Text to Speech and Beyond
Experiments on LJSpeech datasets demonstrate that Speech-T 1) is more robust than the attention based autoregressive TTS model due to its inherent monotonic alignments between text and speech; 2) naturally supports streaming TTS with good voice quality; and 3) enjoys the benefit of joint modeling TTS and ASR in a single network.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
Supervised machine learning has several drawbacks that make it difficult to use in many situations.
Graph-based Visual-Semantic Entanglement Network for Zero-shot Image Recognition
Zero-shot learning uses semantic attributes to connect the search space of unseen objects.
Multiple Attentional Pyramid Networks for Chinese Herbal Recognition
Finally, a new framework for Chinese herbal recognition is proposed as a new application of APN.
Stochastic Region Pooling: Make Attention More Expressive
Global Average Pooling (GAP) is used by default on the channel-wise attention mechanism to extract channel descriptors.
Inner-Imaging Networks: Put Lenses into Convolutional Structure
To deal with these problems, a novel Inner-Imaging architecture is proposed in this paper, which allows relationships between channels to meet the above requirement.
Chinese Herbal Recognition based on Competitive Attentional Fusion of Multi-hierarchies Pyramid Features
According to the characteristics of herbal images, we proposed the competitive attentional fusion pyramid networks to model the features of herbal image, which mdoels the relationship of feature maps from different levels, and re-weights multi-level channels with channel-wise attention mechanism.
Convolutional herbal prescription building method from multi-scale facial features
In order to mine features from different granularities of faces, we design a multi-scale convolutional neural network based on three-grained face, which mines the patient's face information from the organs, local regions, and the entire face.
Competitive Inner-Imaging Squeeze and Excitation for Residual Network
In this work, we propose a competitive squeeze-excitation (SE) mechanism for the residual network.
Tongue image constitution recognition based on Complexity Perception method
To evaluate the performance of our proposed method, we conduct experiments on three sizes of tongue datasets, in which deep convolutional neural network method and traditional digital image analysis method are respectively applied to extract features for tongue images.
Facial Expression Recognition Based on Complexity Perception Classification Algorithm
Facial expression recognition (FER) has always been a challenging issue in computer vision.
Automatic construction of Chinese herbal prescription from tongue image via CNNs and auxiliary latent therapy topics
In order to adapt to the tongue image in a variety of photographic environments and construct herbal prescriptions, a neural network framework for prescription construction is designed.
Supervised Deep Hashing for Hierarchical Labeled Data
Specifically, we define a novel similarity formula for hierarchical labeled data by weighting each layer, and design a deep convolutional neural network to obtain a hash code for each data point.
Conceptualization Topic Modeling
Recently, topic modeling has been widely used to discover the abstract topics in text corpora.
