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Found 19 papers, 2 papers with code
End-to-end Mapping in Heterogeneous Systems Using Graph Representation Learning
To enable heterogeneous computing systems with autonomous programming and optimization capabilities, we propose a unified, end-to-end, programmable graph representation learning (PGL) framework that is capable of mining the complexity of high-level programs down to the universal intermediate representation, extracting the specific computational patterns and predicting which code segments would run best on a specific core in heterogeneous hardware platforms.
Encouraging Disentangled and Convex Representation with Controllable Interpolation Regularization
(2) They lack convexity constraints, which is important for meaningfully manipulating specific attributes for downstream tasks.
Towards Generic Interface for Human-Neural Network Knowledge Exchange
Take image classification as an example, HNI visualizes the reasoning logic of a NN with class-specific Structural Concept Graphs (c-SCG), which are human-interpretable.
Speaker-Oriented Latent Structures for Dialogue-Based Relation Extraction
Dialogue-based relation extraction (DiaRE) aims to detect the structural information from unstructured utterances in dialogues.
Interventional Video Grounding with Dual Contrastive Learning
2) Meanwhile, we introduce a dual contrastive learning approach (DCL) to better align the text and video by maximizing the mutual information (MI) between query and video clips, and the MI between start/end frames of a target moment and the others within a video to learn more informative visual representations.
EMface: Detecting Hard Faces by Exploring Receptive Field Pyraminds
Modern face detectors employ feature pyramids to deal with scale variation.
A Peek Into the Reasoning of Neural Networks: Interpreting with Structural Visual Concepts
Despite substantial progress in applying neural networks (NN) to a wide variety of areas, they still largely suffer from a lack of transparency and interpretability.
Generative Auto-Encoder: Non-adversarial Controllable Synthesis with Disentangled Exploration
DEAE can become a generative model and synthesis semantic controllable samples by interpolating latent code, which can even synthesis novel attribute value never is shown in the original dataset.
Robust Autonomous Landing of UAV in Non-Cooperative Environments based on Dynamic Time Camera-LiDAR Fusion
We have conducted extensive autonomous landing experiments in a variety of familiar or completely unknown environments, verifying that our model can adaptively balance the accuracy and speed, and the UAV can robustly select a safe landing site.
Enhance Gender and Identity Preservation in Face Aging Simulation for Infants and Toddlers
We trained our model using the publicly available UTKFace dataset and evaluated our model by simulating up to 100 years of aging on 1, 156 male and 1, 207 female infant and toddler face photos.
Batch Sequential Adaptive Designs for Global Optimization
The computation burden of the new method is much lighter, and the points clustering is also avoided.
A Vertex Cut based Framework for Load Balancing and Parallelism Optimization in Multi-core Systems
High-level applications, such as machine learning, are evolving from simple models based on multilayer perceptrons for simple image recognition to much deeper and more complex neural networks for self-driving vehicle control systems. The rapid increase in the consumption of memory and computational resources by these models demands the use of multi-core parallel systems to scale the execution of the complex emerging applications that depend on them.
Template-Instance Loss for Offline Handwritten Chinese Character Recognition
The long-standing challenges for offline handwritten Chinese character recognition (HCCR) are twofold: Chinese characters can be very diverse and complicated while similarly looking, and cursive handwriting (due to increased writing speed and infrequent pen lifting) makes strokes and even characters connected together in a flowing manner.
Vehicle Detection in Deep Learning
Computer vision is developing rapidly with the support of deep learning techniques.
A Supervised STDP-based Training Algorithm for Living Neural Networks
Neural networks have shown great potential in many applications like speech recognition, drug discovery, image classification, and object detection.
Complexity-Adaptive Distance Metric for Object Proposals Generation
Distance metric plays a key role in grouping superpixels to produce object proposals for object detection.
1-HKUST: Object Detection in ILSVRC 2014
We participated in the object detection track of ILSVRC 2014 and received the fourth place among the 38 teams.
Shadow Removal from Single RGB-D Images
We present the first automatic method to remove shadows from single RGB-D images.
