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Found 6 papers, 1 papers with code
Instance-incremental Scene Graph Generation from Real-world Point Clouds via Normalizing Flows
This work introduces a new task of instance-incremental scene graph generation: Given a scene of the point cloud, representing it as a graph and automatically increasing novel instances.
Neighborhood Spatial Aggregation MC Dropout for Efficient Uncertainty-aware Semantic Segmentation in Point Clouds
Specifically, the NSA-MC dropout samples the model many times through a space-dependent way, outputting point-wise distribution by aggregating stochastic inference results of neighbors.
In-field early disease recognition of potato late blight based on deep learning and proximal hyperspectral imaging
Effective early detection of potato late blight (PLB) is an essential aspect of potato cultivation.
Tea Chrysanthemum Detection under Unstructured Environments Using the TC-YOLO Model
Tea chrysanthemum detection at its flowering stage is one of the key components for selective chrysanthemum harvesting robot development.
Representation Learning-Assisted Click-Through Rate Prediction
These subnets model the user-ad, ad-ad and feature-CTR relationship respectively.
Ranked #2 on
Click-Through Rate Prediction
on Avito
Neural Response Generation via GAN with an Approximate Embedding Layer
This paper presents a Generative Adversarial Network (GAN) to model single-turn short-text conversations, which trains a sequence-to-sequence (Seq2Seq) network for response generation simultaneously with a discriminative classifier that measures the differences between human-produced responses and machine-generated ones.
