An overview of cross-media retrieval: Concepts, methodologies, benchmarks, and challenges
Multimedia retrieval plays an indispensable role in big data utilization. Past efforts mainly
focused on single-media retrieval. However, the requirements of users are highly flexible …
focused on single-media retrieval. However, the requirements of users are highly flexible …
Resilience and resilient systems of artificial intelligence: taxonomy, models and methods
Artificial intelligence systems are increasingly being used in industrial applications, security
and military contexts, disaster response complexes, policing and justice practices, finance …
and military contexts, disaster response complexes, policing and justice practices, finance …
Single image dehazing via conditional generative adversarial network
In this paper, we present an algorithm to directly restore a clear image from a hazy image.
This problem is highly ill-posed and most existing algorithms often use hand-crafted …
This problem is highly ill-posed and most existing algorithms often use hand-crafted …
Host–parasite: Graph LSTM-in-LSTM for group activity recognition
This article aims to tackle the problem of group activity recognition in the multiple-person
scene. To model the group activity with multiple persons, most long short-term memory …
scene. To model the group activity with multiple persons, most long short-term memory …
Weakly-supervised semantic guided hashing for social image retrieval
Hashing has been widely investigated for large-scale image retrieval due to its search
effectiveness and computation efficiency. In this work, we propose a novel Semantic Guided …
effectiveness and computation efficiency. In this work, we propose a novel Semantic Guided …
Small object detection in unmanned aerial vehicle images using feature fusion and scaling-based single shot detector with spatial context analysis
X Liang, J Zhang, L Zhuo, Y Li… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Objects in unmanned aerial vehicle (UAV) images are generally small due to the high-
photography altitude. Although many efforts have been made in object detection, how to …
photography altitude. Although many efforts have been made in object detection, how to …
Learning dual convolutional neural networks for low-level vision
In this paper, we propose a general dual convolutional neural network (DualCNN) for low-
level vision problems, eg, super-resolution, edge-preserving filtering, deraining and …
level vision problems, eg, super-resolution, edge-preserving filtering, deraining and …
Global-feature encoding U-Net (GEU-Net) for multi-focus image fusion
The convolutional neural network (CNN)-based multi-focus image fusion methods which
learn the focus map from the source images have greatly enhanced fusion performance …
learn the focus map from the source images have greatly enhanced fusion performance …
Meta-learning-based incremental few-shot object detection
M Cheng, H Wang, Y Long - … on Circuits and Systems for Video …, 2021 - ieeexplore.ieee.org
Recent years have witnessed meaningful progress in the task of few-shot object detection.
However, most of the existing models are not capable of incremental learning with a few …
However, most of the existing models are not capable of incremental learning with a few …
Weakly supervised deep matrix factorization for social image understanding
The number of images associated with weakly supervised user-provided tags has increased
dramatically in recent years. User-provided tags are incomplete, subjective and noisy. In this …
dramatically in recent years. User-provided tags are incomplete, subjective and noisy. In this …