Image Processing
The dataset contains results of the paper being submitted.
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This repository contains code to apply the ESPER method to quasi-continuum models of biomolecules exhibiting multiple degrees of freedom, as described in Seitz et al. (2022, IEEE TCI). As inputs into ESPER, detailed instructions are also provided for generating custom synthetic datasets with increasing complexity to mirror known cryo-EM image attributes.
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Currency recognition and classification is one essential task to do. Both paper and coin currency play important role in transactions in everyday life. But provided there are many datasets available of paper currency, and very less datasets are available of coin currency. Coin currency recognition becomes important because even though the amount for which people do coin transactions is small but inaccuracy in recognition can lead to huge loss. Following are the objectives to create this dataset:
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Cryo-EM dataset of 80S ribosomes from yeast. This dataset has been described in Dashti et al. (2014, PNAS) "Trajectories of the ribosome as a Brownian nanomachine". In that study, a subset of the dataset was used to demonstrate the performance of a machine learning technique (now termed ManifoldEM) using manifold embedding to determine the energy landscape of a molecule. The dataset is re-analyzed in Seitz et al.
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This project investigates bias in automatic facial recognition (FR). Specifically, subjects are grouped into predefined subgroups based on gender, ethnicity, and age. We propose a novel image collection called Balanced Faces in the Wild (BFW), which is balanced across eight subgroups (i.e., 800 face images of 100 subjects, each with 25 face samples).
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The experimental data in this paper comes from the bamboo sticks provided by farmers who sell bamboo in Anji. We randomly grab less than 100 bamboo sticks and bundle them together. The heights of 5cm, 10cm, 15cm, and 20cm were taken from the front and left and right inclination to take pictures, screen clear and effective experimental data, and then use labelimg software to label them. The sparse bamboo stick samples collected were 600.
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data
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This dataset contains 1050 multi-pattern multi-bin wafer bin maps (WBMs) synthesized from WM-811K binary WBM dataset and real world multi-bin WBMs using a trained pix2pix model.
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A crowdsourcing subjective evaluation of viewport images obtained with several sphere-to-plane projections was conducted. The viewport images were rendered from eight omnidirectional images in equirectangular format. The pairwise comparison (PC) method was chosen for the subjective evaluation of projections. More details about the viewport images and subjective evaluation procedure can be found in [1].
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