AIMC Topic: Algorithms

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HandVoxNet++: 3D Hand Shape and Pose Estimation Using Voxel-Based Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
3D hand shape and pose estimation from a single depth map is a new and challenging computer vision problem with many applications. Existing methods addressing it directly regress hand meshes via 2D convolutional neural networks, which leads to artifa...

Self-Supervised Human Detection and Segmentation via Background Inpainting.

IEEE transactions on pattern analysis and machine intelligence
While supervised object detection and segmentation methods achieve impressive accuracy, they generalize poorly to images whose appearance significantly differs from the data they have been trained on. To address this when annotating data is prohibiti...

Deep Learning for HDR Imaging: State-of-the-Art and Future Trends.

IEEE transactions on pattern analysis and machine intelligence
High dynamic range (HDR) imaging is a technique that allows an extensive dynamic range of exposures, which is important in image processing, computer graphics, and computer vision. In recent years, there has been a significant advancement in HDR imag...

Learn to Predict Sets Using Feed-Forward Neural Networks.

IEEE transactions on pattern analysis and machine intelligence
This paper addresses the task of set prediction using deep feed-forward neural networks. A set is a collection of elements which is invariant under permutation and the size of a set is not fixed in advance. Many real-world problems, such as image tag...

A Topological Loss Function for Deep-Learning Based Image Segmentation Using Persistent Homology.

IEEE transactions on pattern analysis and machine intelligence
We introduce a method for training neural networks to perform image or volume segmentation in which prior knowledge about the topology of the segmented object can be explicitly provided and then incorporated into the training process. By using the di...

Adverse Weather Target Detection Algorithm Based on Adaptive Color Levels and Improved YOLOv5.

Sensors (Basel, Switzerland)
With the continuous development of artificial intelligence and computer vision technology, autonomous vehicles have developed rapidly. Although self-driving vehicles have achieved good results in normal environments, driving in adverse weather can st...

A Fissure-Aided Registration Approach for Automatic Pulmonary Lobe Segmentation Using Deep Learning.

Sensors (Basel, Switzerland)
The segmentation of pulmonary lobes is important in clinical assessment, lesion location, and surgical planning. Automatic lobe segmentation is challenging, mainly due to the incomplete fissures or the morphological variation resulting from lung dise...

Using machine-learning strategies to solve psychometric problems.

Scientific reports
Validating scales for clinical use is a common procedure in medicine and psychology. Through the application of computational methods, we present a new strategy for estimating construct validity and criterion validity. XGBoost, Random Forest and Supp...

MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition.

PloS one
In the field of surface electromyography (sEMG) gesture recognition, how to improve recognition accuracy has been a research hotspot. The rapid development of deep learning provides a new solution to this problem. At present, the main applications of...

The Deep Learning Method Differentiates Patients with Bipolar Disorder from Controls with High Accuracy Using EEG Data.

Clinical EEG and neuroscience
Bipolar disorder (BD) is a mental disorder characterized by depressive and manic or hypomanic episodes. The complexity in the diagnosis of Bipolar disorder (BD) due to its overlapping symptoms with other mood disorders prompted researchers and clini...