Search Results for author:
Found 11 papers, 3 papers with code
The Right Losses for the Right Gains: Improving the Semantic Consistency of Deep Text-to-Image Generation with Distribution-Sensitive Losses
We test this approach on two baseline models: SSAGAN and AttnGAN (with style blocks to enhance the fine-grained details of the images.)
Dataset Creation Pipeline for Camera-Based Heart Rate Estimation
The data prepared is to include camera frames as well as sensor readings from an electrocardiograph sensor.
Pervasive Hand Gesture Recognition for Smartphones using Non-audible Sound and Deep Learning
The third method adopts late fusion by having two convectional input branches processing each of the dual-channel spectrograms and then the outputs are merged by the last layers.
Enhanced 3D Myocardial Strain Estimation from Multi-View 2D CMR Imaging
In this paper, we propose an enhanced 3D myocardial strain estimation procedure, which combines complementary displacement information from multiple orientations of a single imaging modality (untagged CMR SSFP images).
Veritas Annotator: Discovering the Origin of a Rumour
Defined as the intentional or unintentionalspread of false information (K et al., 2019)through context and/or content manipulation, fake news has become one of the most seriousproblems associated with online information(Waldrop, 2017).
A Hybrid Deep Learning Approach for Texture Analysis
Texture classification is a problem that has various applications such as remote sensing and forest species recognition.
CIFAR-10: KNN-based Ensemble of Classifiers
In this paper, we study the performance of different classifiers on the CIFAR-10 dataset, and build an ensemble of classifiers to reach a better performance.
House price estimation from visual and textual features
Most existing automatic house price estimation systems rely only on some textual data like its neighborhood area and the number of rooms.
Reactive Collision Avoidance using Evolutionary Neural Networks
A single front-facing rangefinder sensor is the only input required by our method.
GAdaBoost: Accelerating Adaboost Feature Selection with Genetic Algorithms
This is due to the vast features space and the exhaustive search nature of Adaboost.
Applying deep learning to classify pornographic images and videos
Unfortunately, these methods require vast experience to design the classifier including one or more of the popular computer vision feature descriptors.
