Zaloguj się

Gotowe bibliografie tematyczne / REAL IMAGE PREDICTION

Spis treści

Artykuły w czasopismach

Gotowa bibliografia na temat „REAL IMAGE PREDICTION”

Autor: Grafiati

Data publikacji: 11 września 2023

Utwórz poprawne odniesienie w stylach APA, MLA, Chicago, Harvard i wielu innych

Wybierz rodzaj źródła:

Zobacz listy aktualnych artykułów, książek, rozpraw, streszczeń i innych źródeł naukowych na temat „REAL IMAGE PREDICTION”.

Przycisk „Dodaj do bibliografii” jest dostępny obok każdej pracy w bibliografii. Użyj go – a my automatycznie utworzymy odniesienie bibliograficzne do wybranej pracy w stylu cytowania, którego potrzebujesz: APA, MLA, Harvard, Chicago, Vancouver itp.

Możesz również pobrać pełny tekst publikacji naukowej w formacie „.pdf” i przeczytać adnotację do pracy online, jeśli odpowiednie parametry są dostępne w metadanych.

Artykuły w czasopismach na temat "REAL IMAGE PREDICTION"

1

Takezawa, Takuma, and Yukihiko Yamashita. "Wavelet Based Image Coding via Image Component Prediction Using Neural Networks." International Journal of Machine Learning and Computing 11, no. 2 (2021): 137–42. http://dx.doi.org/10.18178/ijmlc.2021.11.2.1026.

Pełny tekst źródła

Streszczenie:

In the process of wavelet based image coding, it is possible to enhance the performance by applying prediction. However, it is difficult to apply the prediction using a decoded image to the 2D DWT which is used in JPEG2000 because the decoded pixels are apart from pixels which should be predicted. Therefore, not images but DWT coefficients have been predicted. To solve this problem, predictive coding is applied for one-dimensional transform part in 2D DWT. Zhou and Yamashita proposed to use half-pixel line segment matching for the prediction of wavelet based image coding with prediction. In th

Style APA, Harvard, Vancouver, ISO itp.

2

Hong, Yan, Li Niu, and Jianfu Zhang. "Shadow Generation for Composite Image in Real-World Scenes." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 1 (2022): 914–22. http://dx.doi.org/10.1609/aaai.v36i1.19974.

Pełny tekst źródła

Streszczenie:

Image composition targets at inserting a foreground object into a background image. Most previous image composition methods focus on adjusting the foreground to make it compatible with background while ignoring the shadow effect of foreground on the background. In this work, we focus on generating plausible shadow for the foreground object in the composite image. First, we contribute a real-world shadow generation dataset DESOBA by generating synthetic composite images based on paired real images and deshadowed images. Then, we propose a novel shadow generation network SGRNet, which consists o

Style APA, Harvard, Vancouver, ISO itp.

3

Sather, A. P., S. D. M. Jones, and D. R. C. Bailey. "Real-time ultrasound image analysis for the estimation of carcass yield and pork quality." Canadian Journal of Animal Science 76, no. 1 (1996): 55–62. http://dx.doi.org/10.4141/cjas96-008.

Pełny tekst źródła

Streszczenie:

Average backfat thickness measurements (liveweight of 92.5 kg) were made on 276 pigs using the Krautkramer USK7 ultrasonic machine. Immediately preceding and 1 h after slaughter real-time ultrasonic images were made between the 3rd and 4th last ribs with the Tokyo Keiki LS-1000 (n = 149) and/or CS-3000 (n = 240) machines. Image analysis software was used to measure fat thickness (FT), muscle depth (MD) and area (MA) as well as scoring the number of objects, object area and percentage object area of the loin to be used for predicting meat quality. Carcasses were also graded by the Hennessy Grad

Style APA, Harvard, Vancouver, ISO itp.

4

Tham, Hwee Sheng, Razaidi Hussin, and Rizalafande Che Ismail. "A Real-Time Distance Prediction via Deep Learning and Microsoft Kinect." IOP Conference Series: Earth and Environmental Science 1064, no. 1 (2022): 012048. http://dx.doi.org/10.1088/1755-1315/1064/1/012048.

Pełny tekst źródła

Streszczenie:

Abstract 3D(Dimension) understanding has become the herald of computer vision and graphics research in the era of technology. It benefits many applications such as autonomous cars, robotics, and medical image processing. The pros and cons of 3D detection bring convenience to the human community instead of 2D detection. The 3D detection consists of RGB (Red, Green and Blue) colour images and depth images which are able to perform better than 2D in real. The current technology is relying on the high costing light detection and ranging (LiDAR). However, the use of Microsoft Kinect has replaced th

Style APA, Harvard, Vancouver, ISO itp.

5

Pintelas, Emmanuel, Meletis Liaskos, Ioannis E. Livieris, Sotiris Kotsiantis, and Panagiotis Pintelas. "Explainable Machine Learning Framework for Image Classification Problems: Case Study on Glioma Cancer Prediction." Journal of Imaging 6, no. 6 (2020): 37. http://dx.doi.org/10.3390/jimaging6060037.

Pełny tekst źródła

Streszczenie:

Image classification is a very popular machine learning domain in which deep convolutional neural networks have mainly emerged on such applications. These networks manage to achieve remarkable performance in terms of prediction accuracy but they are considered as black box models since they lack the ability to interpret their inner working mechanism and explain the main reasoning of their predictions. There is a variety of real world tasks, such as medical applications, in which interpretability and explainability play a significant role. Making decisions on critical issues such as cancer pred

Style APA, Harvard, Vancouver, ISO itp.

6

Snider, Eric J., Sofia I. Hernandez-Torres, and Ryan Hennessey. "Using Ultrasound Image Augmentation and Ensemble Predictions to Prevent Machine-Learning Model Overfitting." Diagnostics 13, no. 3 (2023): 417. http://dx.doi.org/10.3390/diagnostics13030417.

Pełny tekst źródła

Streszczenie:

Deep learning predictive models have the potential to simplify and automate medical imaging diagnostics by lowering the skill threshold for image interpretation. However, this requires predictive models that are generalized to handle subject variability as seen clinically. Here, we highlight methods to improve test accuracy of an image classifier model for shrapnel identification using tissue phantom image sets. Using a previously developed image classifier neural network—termed ShrapML—blind test accuracy was less than 70% and was variable depending on the training/test data setup, as determi

Style APA, Harvard, Vancouver, ISO itp.

7

Froning, Dieter, Eugen Hoppe, and Ralf Peters. "The Applicability of Machine Learning Methods to the Characterization of Fibrous Gas Diffusion Layers." Applied Sciences 13, no. 12 (2023): 6981. http://dx.doi.org/10.3390/app13126981.

Pełny tekst źródła

Streszczenie:

Porous materials can be characterized by well-trained neural networks. In this study, fibrous paper-type gas diffusion layers were trained with artificial data created by a stochastic geometry model. The features of the data were calculated by means of transport simulations using the Lattice–Boltzmann method based on stochastic micro-structures. A convolutional neural network was developed that can predict the permeability and tortuosity of the material, through-plane and in-plane. The characteristics of real data, both uncompressed and compressed, were predicted. The data were represented by

Style APA, Harvard, Vancouver, ISO itp.

8

Moskolaï, Waytehad Rose, Wahabou Abdou, Albert Dipanda, and Kolyang. "Application of Deep Learning Architectures for Satellite Image Time Series Prediction: A Review." Remote Sensing 13, no. 23 (2021): 4822. http://dx.doi.org/10.3390/rs13234822.

Pełny tekst źródła

Streszczenie:

Satellite image time series (SITS) is a sequence of satellite images that record a given area at several consecutive times. The aim of such sequences is to use not only spatial information but also the temporal dimension of the data, which is used for multiple real-world applications, such as classification, segmentation, anomaly detection, and prediction. Several traditional machine learning algorithms have been developed and successfully applied to time series for predictions. However, these methods have limitations in some situations, thus deep learning (DL) techniques have been introduced

Style APA, Harvard, Vancouver, ISO itp.

9

Rajesh, E., Shajahan Basheer, Rajesh Kumar Dhanaraj, et al. "Machine Learning for Online Automatic Prediction of Common Disease Attributes Using Never-Ending Image Learner." Diagnostics 13, no. 1 (2022): 95. http://dx.doi.org/10.3390/diagnostics13010095.

Pełny tekst źródła

Streszczenie:

The rapid increase in Internet technology and machine-learning devices has opened up new avenues for online healthcare systems. Sometimes, getting medical assistance or healthcare advice online is easier to understand than getting it in person. For mild symptoms, people frequently feel reluctant to visit the hospital or a doctor; instead, they express their questions on numerous healthcare forums. However, predictions may not always be accurate, and there is no assurance that users will always receive a reply to their posts. In addition, some posts are made up, which can misdirect the patient.

Style APA, Harvard, Vancouver, ISO itp.

10

Bhimte, Sumit, Hrishikesh hasabnis, Rohit Shirsath, Saurabh Sonar, and Mahendra Salunke. "Severity Prediction System for Real Time Pothole Detection." Journal of University of Shanghai for Science and Technology 23, no. 07 (2021): 1328–34. http://dx.doi.org/10.51201/jusst/21/07356.

Pełny tekst źródła

Streszczenie:

Pothole Detection System using Image Processing or using Accelerometer is not a new normal. But there is no real time application which utilizes both techniques to provide us with efficient solution. We present a system which can be useful for the drivers to determine the intensity of Pothole using both Image Processing Technology and Accelerometer device-based Algorithm. The challenge in building this system was to efficiently detect a Pothole present in roads, to analyze the severity of Pothole and to provide users with information like Road Quality and best possible route. We have used vari

Style APA, Harvard, Vancouver, ISO itp.

Więcej źródeł

Oferujemy zniżki na wszystkie plany premium dla autorów, których prace zostały uwzględnione w tematycznych zestawieniach literatury. Skontaktuj się z nami, aby uzyskać unikalny kod promocyjny!