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InverseForm: A Loss Function for Structured Boundary-Aware Segmentation
We present a novel boundary-aware loss term for semantic segmentation us...
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Hero: On the Chaos When PATH Meets Modules
Ever since its first release in 2009, the Go programming language (Golan...
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SWA Object Detection
Do you want to improve 1.0 AP for your object detector without any infer...
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VC-Net: Deep Volume-Composition Networks for Segmentation and Visualization of Highly Sparse and Noisy Image Data
The motivation of our work is to present a new visualization-guided comp...
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VarifocalNet: An IoU-aware Dense Object Detector
Accurately ranking a huge number of candidate detections is a key to the...
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Automatic Speech Summarisation: A Scoping Review
Speech summarisation techniques take human speech as input and then outp...
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Differentiable Joint Pruning and Quantization for Hardware Efficiency
We present a differentiable joint pruning and quantization (DJPQ) scheme...
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Multi-level colonoscopy malignant tissue detection with adversarial CAC-UNet
The automatic and objective medical diagnostic model can be valuable to ...
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Will Dependency Conflicts Affect My Program's Semantics?
Java projects are often built on top of various third-party libraries. I...
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Bayesian Bits: Unifying Quantization and Pruning
We introduce Bayesian Bits, a practical method for joint mixed precision...
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Combining GHOST and Casper
We present "Gasper," a proof-of-stake-based consensus protocol, which is...
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Interactive, Effort-Aware Library Version Harmonization
As a mixed result of intensive dependency on third-party libraries, flex...
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An Empirical Study of Usages, Updates and Risks of Third-Party Libraries in Java Projects
Third-party libraries are a central building block to develop software s...
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LiDAR Iris for Loop-Closure Detection
In this paper, a global descriptor for a LiDAR point cloud, called LiDAR...
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Breast Anatomy Enriched Tumor Saliency Estimation
Breast cancer investigation is of great significance, and developing tum...
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Refined-Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants
Accurate segmentation of punctate white matter lesion (PWML) in infantil...
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Tumor Saliency Estimation for Breast Ultrasound Images via Breast Anatomy Modeling
Tumor saliency estimation aims to localize tumors by modeling the visual...
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Neural Response Generation with Meta-Words
We present open domain response generation with meta-words. A meta-word ...
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Inpatient2Vec: Medical Representation Learning for Inpatients
Representation learning (RL) plays an important role in extracting prope...
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Modified integral imaging reconstruction and encryption using an improved SR reconstruction algorithm
We propose a monospectral image encryption method in which the multispec...
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A Hybrid Framework for Tumor Saliency Estimation
Automatic tumor segmentation of breast ultrasound (BUS) image is quite c...
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Delay Analysis of Random Scheduling and Round Robin in Small Cell Networks
We analyze the delay performance of small cell networks operating under ...
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A Benchmark for Breast Ultrasound Image Segmentation (BUSIS)
Breast ultrasound (BUS) image segmentation is challenging and critical f...
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An Adaptive Gas Cost Mechanism for Ethereum to Defend Against Under-Priced DoS Attacks
The gas mechanism in Ethereum charges the execution of every operation t...
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Review. Machine learning techniques for traffic sign detection
An automatic road sign detection system localizes road signs from within...
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Restricting Greed in Training of Generative Adversarial Network
Generative adversarial network (GAN) has gotten wide re-search interest ...
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10,000+ Times Accelerated Robust Subset Selection (ARSS)
Subset selection from massive data with noised information is increasing...
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Effective Spectral Unmixing via Robust Representation and Learning-based Sparsity
Hyperspectral unmixing (HU) plays a fundamental role in a wide range of ...
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Structured Sparse Method for Hyperspectral Unmixing
Hyperspectral Unmixing (HU) has received increasing attention in the pas...
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Robust Hyperspectral Unmixing with Correntropy based Metric
Hyperspectral unmixing is one of the crucial steps for many hyperspectra...
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