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Found 6 papers, 1 papers with code
A Sequence Agnostic Multimodal Preprocessing for Clogged Blood Vessel Detection in Alzheimer's Diagnosis
Successful identification of blood vessel blockage is a crucial step for Alzheimer's disease diagnosis.
Lung-Originated Tumor Segmentation from Computed Tomography Scan (LOTUS) Benchmark
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor.
Anatomy-XNet: An Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification in Chest X-rays
We adopt a semi-supervised learning method by utilizing available small-scale organ-level annotations to locate the anatomy regions in large-scale datasets where the organ-level annotations are absent.
Ranked #15 on
Multi-Label Classification
on CheXpert
Let's Vibrate with Vibration: Augmenting Structural Engineering with Low-Cost Vibration Sensing
Nonetheless, in the rarely explored time domain, our analyses reveal a novel modality of relation between vibration generated at different heights of a structure and the associated height, which was explored in the frequency domain earlier in the literature with expensive sensors.
DFR-TSD: A Deep Learning Based Framework for Robust Traffic Sign Detection Under Challenging Weather Conditions
However, the SOTA (SOTA) methods have been evaluated on clean and challenge-free datasets and overlooked the performance deterioration associated with different challenging conditions (CCs) that obscure the traffic images captured in the wild.
Automatic Traffic Sign Detection and Recognition Using SegU-Net and a Modified Tversky Loss Function With L1-Constraint
In this paper, we look at traffic sign detection as an image segmentation problem and propose a deep convolutional neural network-based approach to solve it.
