Search Results for author:
Found 16 papers, 5 papers with code
Somatomotor-Visual Resting State Functional Connectivity Increases After Two Years in the UK Biobank Longitudinal Cohort
Using the full FC and a training set of 2, 000 subjects, one is able to predict which scan is older 82. 5\% of the time using either the full Power264 FC or the UKB-provided ICA-based FC.
TMHOI: Translational Model for Human-Object Interaction Detection
Our method effectively captures the sentiment representation of HOIs by integrating both spatial and semantic knowledge.
Computational Efficiency
Human-Object Interaction Detection
+1
Gradient-Guided Knowledge Distillation for Object Detectors
In this paper, we propose a novel approach for knowledge distillation in object detection, named Gradient-guided Knowledge Distillation (GKD).
Visual Saliency-Guided Channel Pruning for Deep Visual Detectors in Autonomous Driving
Deep neural network (DNN) pruning has become a de facto component for deploying on resource-constrained devices since it can reduce memory requirements and computation costs during inference.
Comparison Of Deep Object Detectors On A New Vulnerable Pedestrian Dataset
YOLOX consistently outperforms all other detectors on the mAP (0. 5:0. 95) per class metric, obtaining 0. 5644, 0. 5242, 0. 4781, and 0. 6796 for Children Without Disability, Elderly Without Disability, Non-vulnerable, and With Disability, respectively.
Enhancing Accuracy and Robustness of Steering Angle Prediction with Attention Mechanism
In this paper, our focus is on enhancing steering angle prediction for autonomous driving tasks.
Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength
The aim of this paper is to design a deep learning-based model to predict proximal femoral strength using multi-view information fusion.
Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios
Experiments show that the proposed attack targeting the objectness aspect is 45. 17% and 43. 50% more effective than those generated from classification and/or localization losses on the KITTI and COCO traffic datasets, respectively.
Adaptive Instance Distillation for Object Detection in Autonomous Driving
In this paper, we propose Adaptive Instance Distillation (AID) to selectively impart teacher's knowledge to the student to improve the performance of knowledge distillation.
Improving Apparel Detection with Category Grouping and Multi-grained Branches
In particular, we improve the mAP for last 30% categories (in terms of training sample number) by 2. 6 and 4. 6 for DeepFashion2 and OpenImagesV4-Clothing, respectively.
Grow-Push-Prune: aligning deep discriminants for effective structural network compression
We also show that our grown Inception nets (without hard-coded dimension alignment) clearly outperform residual nets of similar complexities.
Unsupervised Domain Adaptation Through Transferring both the Source-Knowledge and Target-Relatedness Simultaneously
Unsupervised domain adaptation (UDA) is an emerging research topic in the field of machine learning and pattern recognition, which aims to help the learning of unlabeled target domain by transferring knowledge from the source domain.
Task dependent Deep LDA pruning of neural networks
Moreover, we examine our approach's potential in network architecture search for specific tasks and analyze the influence of our pruning on model robustness to noises and adversarial attacks.
Efficient Gender Classification Using a Deep LDA-Pruned Net
Many real-time tasks, such as human-computer interaction, require fast and efficient facial gender classification.
Joint Gender Classification and Age Estimation by Nearly Orthogonalizing Their Semantic Spaces
In human face-based biometrics, gender classification and age estimation are two typical learning tasks.
A Unified Gender-Aware Age Estimation
Although leading to promotion of age estimation performance, such a concatenation not only likely confuses the semantics between the gender and age, but also ignores the aging discrepancy between the male and the female.
