This paper explores a better prediction target for BERT pre-training of vision transformers. We observe that current targets disagree with human perception judgment. contradiction motivates us to learn perceptual target. argue perceptually similar images should stay close each other in the space. surprisingly find one simple yet effective idea: enforcing similarity during dVAE training. Moreover, we adopt self-supervised transformer model deep feature extraction and show it works well...

With basic Semi-Supervised Object Detection (SSOD) techniques, one-stage detectors generally obtain limited promotions compared with two-stage clusters. We experimentally find that the root lies in two kinds of ambiguities: (1) Selection ambiguity selected pseudo labels are less accurate, since classification scores cannot properly represent localization quality. (2) Assignment samples matched improper pseudo-label assignment, as strategy is misguided by missed objects and inaccurate boxes....

Multi-Target Multi-Camera tracking (MTMC) is an essential task in the intelligent city and traffic analysis. It a great challenging due to several problems such as heavy occlusions appearance variance caused by various camera perspectives congested vehicles. In this paper, we propose practical framework for dealing with MTMC problem. The proposed contains three stage. Firstly, vehicles detection Re-ID stage, system leverages Cascade R-CNN detect all extract features module cameras. Secondly,...

Drug resistance is a critical impediment to efficient therapy of diffuse large B-cell lymphoma (DLBCL) patients. Recent studies have highlighted the association between ferroptosis and drug that has been reported. Fatty acid synthase (FASN) always related poor prognosis. In this study, we investigate impact FASN on in DLBCL explore its potential modulation mechanisms. The clinical correlation mRNA expression was first analyzed confirm role based TCGA database. Next, investigated vitro vivo....

This paper explores a better prediction target for BERT pre-training of vision transformers. We observe that current targets disagree with human perception judgment.This contradiction motivates us to learn perceptual target. argue perceptually similar images should stay close each other in the space. surprisingly find one simple yet effective idea: enforcing similarity during dVAE training. Moreover, we adopt self-supervised transformer model deep feature extraction and show it works well...

The fast evolution and widespread of deepfake techniques in real-world scenarios require stronger generalization abilities face forgery detectors. Some works capture the features that are unrelated to method-specific artifacts, such as clues blending boundary, accumulated up-sampling, strengthen ability. However, effectiveness these methods can be easily corrupted by post-processing operations compression. Inspired transfer learning, neural networks pre-trained on other large-scale...

Current state-of-the-art semi-supervised semantic segmentation (SSSS) methods typically adopt pseudo labeling and consistency regularization between multiple learners with different perturbations. Although the performance is desirable, many issues remain: (1) supervisions from a single learner tend to be noisy which causes unreliable (2) existing pixel-wise confidence-score-based reliability measurement potential error accumulation as training proceeds. In this paper, we propose novel SSSS...

An up-to-date city-scale lane-level map is an indispensable infrastructure and a key enabling technology for ensuring the safety user experience of autonomous driving systems.In industrial scenarios, reliance on manual annotation updates creates critical bottleneck.Lane-level require precise change information must ensure consistency with adjacent data while adhering to strict standards.Traditional methods utilize three-stage approach-construction, detection, updating-which often...

Purpose – The purpose of this paper is to design a special automatic redundant robot painting system (RRPS), which can automatically navigate and paint in the long non-regular duct. Design/methodology/approach RRPS designed with three subsystems: robot, spraying control safety system. Based on modular theory, falls naturally into mobile platform, 4-DOF location mechanism 10-DOF manipulator. restriction distance between links duct axis used plan trajectory manipulator so that it would not...

The task of live traffic condition prediction, which aims at predicting conditions (i.e., fast, slow, and congested) based on information roads, plays a vital role in intelligent transportation systems, such as navigation, route planning, ride-hailing services. Existing solutions have adopted aggregated trajectory data to generate estimates, inevitably suffer from GPS drift caused by cluttered urban road scenarios. In addition, the alone is insufficient provide evidence for sudden situations...

This paper presents GoodSAM++, a novel framework utilizing the powerful zero-shot instance segmentation capability of SAM (i.e., teacher) to learn compact panoramic semantic model, i.e., student, without requiring any labeled data. GoodSAM++ addresses two critical challenges: 1) SAM's inability provide labels and inherent distortion problems images; 2) significant capacity disparity between student. The `out-of-the-box' insight is introduce teacher assistant (TA) information for SAM,...

Background and Aims: Liver inflammation is important in guiding the initiation of antiviral treatment affects progression chronic hepatitis B(CHB). The soluble programmed cell death 1 protein (sPD-1) was upregulated inflammatory infectious diseases correlated with disease severity. We aimed to investigate correlation between serum sPD-1 levels liver CHB patients their role indicating inflammation. Methods: 241 who underwent biopsy were enrolled. degree analyzed. Univariate multivariate...

Copy-Paste is a simple and effective data augmentation strategy for instance segmentation. By randomly pasting object instances onto new background images, it creates training free significantly boosts the segmentation performance, especially rare categories. Although diverse, high-quality used in result more performance gain, previous works utilize either from human-annotated datasets or rendered 3D models, both approaches are too expensive to scale up obtain good diversity. In this paper,...

This paper tackles a novel yet challenging problem: how to transfer knowledge from the emerging Segment Anything Model (SAM) -- which reveals impressive zero-shot instance segmentation capacity learn compact panoramic semantic model, i.e., student, without requiring any labeled data. poses considerable challenges due SAM's inability provide labels and large gap between SAM student. To this end, we propose framework, called GoodSAM, that introduces teacher assistant (TA) information,...

Generating city-scale lane-level maps faces significant challenges due to the intricate urban environments, such as blurred or absent lane markings. Additionally, a standard map requires comprehensive organization of groupings, encompassing direction, style, boundary, and topology, yet has not been thoroughly examined in prior research. These obstacles result labor-intensive human annotation high maintenance costs. This paper overcomes these limitations presents an industrial-grade solution...

Abstract Background and Aims: Liver inflammation is important in guiding the initiation of antiviral treatment affect disease progression chronic hepatitis B(CHB). Soluble programmed cell death 1 protein(sPD-1) was upregulated inflammatory, infectious diseases correlated with severity. We aimed to investigate correlation between serum sPD-1 liver CHB patients role indicating inflammation. Methods: 241 who underwent a biopsy were enrolled. Correlation levels degree analyzed. Univariate...

Background and Aims: Liver inflammation is important in guiding the initiation of antiviral treatment affect disease progression chronic hepatitis B(CHB). Soluble programmed cell death 1 protein(sPD-1) was upregulated inflammatory, infectious diseases correlated with severity. We aimed to investigate correlation between serum sPD-1 liver CHB patients role indicating inflammation.Methods: 241 who underwent a biopsy were enrolled. Correlation levels degree analyzed. Univariate multivariate...

Focused on the availability of command information system, model system is constructed from capability, business function, application process and object firstly.Secondly, index established in principle.Then, evaluation framework designed requirement consistency, function conformance, operational applicability user friendliness, which are analyzed detail.Further, data acquisition channels calculation methods specific described, lays a foundation for system.

We propose bootstrapped masked autoencoders (BootMAE), a new approach for vision BERT pretraining. BootMAE improves the original (MAE) with two core designs: 1) momentum encoder that provides online feature as extra prediction targets; 2) target-aware decoder tries to reduce pressure on memorize target-specific information in The first design is motivated by observation using pretrained MAE extract features target tokens can achieve better pretraining performance. Therefore, we add parallel...