Results 31 to 40 of about 2,716,934 (278)
, 2020 Deep learning models have had a great success in disease classifications using large data pools of skin cancer images or lung X-rays. However, data scarcity has been the roadblock of applying deep learning models directly on prostate multiparametric MRI (
Carver, Eric +11 more
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A deep-learning approach for high-speed Fourier ptychographic microscopy [PDF]
, 2018 We demonstrate a new convolutional neural network architecture to perform Fourier ptychographic Microscopy (FPM) reconstruction, which achieves high-resolution phase recovery with considerably less data than standard FPM.https://www.researchgate.net ...
Li, Yunzhe +5 more
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IEEE Access, 2020 A Steel Plate Rolling Mill (SPM) is a milling machine that uses rollers to press hot slab inputs to produce ferrous or non-ferrous metal plates. To produce high-quality steel plates, it is important to precisely detect and sense values of manufacturing ...
Cheol Young Park +3 more
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Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering, 2016 Developers often wonder how to implement a certain functionality (e.g., how to parse XML files) using APIs. Obtaining an API usage sequence based on an API-related natural language query is very helpful in this regard. Given a query, existing approaches utilize information retrieval models to search for matching API sequences.
Xiaodong Gu 0002 +3 more
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Quantum Information and Computation, 2016 In recent years, deep learning has had a profound impact on machine learning and artificial intelligence. At the same time, algorithms for quantum computers have been shown to efficiently solve some problems that are intractable on conventional, classical computers.
Nathan Wiebe +2 more
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BMC Medical Informatics and Decision Making, 2019 Following publication of the original ...
Muhammad Naseer Bajwa +6 more
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Generalizable and efficient cross‐domain person re‐identification model using deep metric learning
IET Computer Vision, 2023 Most of the successful person re‐ID models conduct supervised training and need a large number of training data. These models fail to generalise well on unseen unlabelled testing sets.
Saba Sadat Faghih Imani +2 more
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Deep Learning in Proteomics [PDF]
PROTEOMICS, 2020 Abstract Proteomics, the study of all the proteins in biological systems, is becoming a data‐rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS) technology, protein expression and post‐translational modifications (PTMs) can be ...
Bo Wen +6 more
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Deep Learning Approaches Based on Transformer Architectures for Image Captioning Tasks
IEEE Access, 2022 This paper focuses on visual attention, a state-of-the-art approach for image captioning tasks within the computer vision research area. We study the impact that different hyperparemeter configurations on an encoder-decoder visual attention architecture ...
Roberto Castro +3 more
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, 2018 We present a novel regularization approach to train neural networks that enjoys better generalization and test error than standard stochastic gradient descent. Our approach is based on the principles of cross-validation, where a validation set is used to
A Hadjidimos +8 more
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