Image restoration aims to restore high-quality images from degraded
coun...
Aphid infestation poses a significant threat to crop production, rural
c...
Aphid infestations can cause extensive damage to wheat and sorghum field...
Aphids are one of the main threats to crops, rural families, and global ...
Elementary trapping sets (ETSs) are the main culprits for the performanc...
Simultaneous multi-index quantification, segmentation, and uncertainty
e...
We propose a general methodology Reliever for fast and reliable changepo...
The widespread use of black box prediction methods has sparked an increa...
The projection operation is a critical component in a wide range of
opti...
Light field (LF) depth estimation is a crucial task with numerous practi...
First-order optimization methods tend to inherently favor certain soluti...
Flexible laryngoscopy is commonly performed by otolaryngologists to dete...
In this study, an optimization model for offline scheduling policy of
lo...
In this paper, we consider the sequential decision problem where the goa...
Vision Transformers have attracted a lot of attention recently since the...
Vision Transformers has demonstrated competitive performance on computer...
The classical algorithms for online learning and decision-making have th...
The classical Perceptron algorithm of Rosenblatt can be used to find a l...
Control of nonlinear uncertain systems is a common challenge in the robo...
High-dimensional changepoint inference that adapts to various change pat...
The paper focuses on a classical tracking model, subspace learning, grou...
Deep neural networks for 3D point cloud classification, such as PointNet...
Local Transformer-based classification models have recently achieved
pro...
Label assignment plays a significant role in modern object detection mod...
In this paper, we propose a dual-module network architecture that employ...
Object Detection with Transformers (DETR) and related works reach or eve...
The paper proposes a semantic clustering based deduction learning by
mim...
The paper focuses on improving the recent plug-and-play patch rescaling
...
Channel attention mechanisms in convolutional neural networks have been
...
Recent image-to-image translation models have shown great success in map...
Crowd estimation is a very challenging problem. The most recent study tr...
The paper proposes a Dynamic ResBlock Generative Adversarial Network
(DR...
Adversarial training based on the maximum classifier discrepancy between...
In this paper, we study stochastic optimization of areas under
precision...
Fingerspelling in sign language has been the means of communicating tech...
Human beings can recognize new objects with only a few labeled examples,...
Recently, several universal methods have been proposed for online convex...
Colonoscopy is a procedure to detect colorectal polyps which are the pri...
Most classification models treat different object classes in parallel an...
The paper proposes a new text recognition network for scene-text images....
Colorectal cancer (CRC) is one of the most common types of cancer with a...
It has been attracting more and more attention to understand the global
...
In many sequential decision making applications, the change of decision ...
To efficiently solve distributed online learning problems with complicat...
In the last decade, the discovery of noncoding RNA(ncRNA) has exploded.
...
Depth estimation and semantic segmentation play essential roles in scene...
Most deep learning models are data-driven and the excellent performance ...
This paper focuses on the problem of online golf ball detection and trac...
Due to the difficulty in acquiring massive task-specific occluded images...
The paper proposes a light-weighted stereo frustums matching module for ...