A5008829329- Adversarial Robustness in Machine Learning
- Domain Adaptation and Few-Shot Learning
- Advanced Neural Network Applications
- Anomaly Detection Techniques and Applications
- Bacillus and Francisella bacterial research
- Cancer Immunotherapy and Biomarkers
- Adenosine and Purinergic Signaling
- Fibroblast Growth Factor Research
- Metabolism and Genetic Disorders
- Video Surveillance and Tracking Methods
- Autophagy in Disease and Therapy
- Healthcare professionals’ stress and burnout
- Thermoregulation and physiological responses
- Web Data Mining and Analysis
- Liver physiology and pathology
- Information Retrieval and Search Behavior
- Immune cells in cancer
- Immune Cell Function and Interaction
- Alzheimer's disease research and treatments
- Biochemical Acid Research Studies
- Hydrological Forecasting Using AI
- Generative Adversarial Networks and Image Synthesis
- Reproductive System and Pregnancy
- Calcium signaling and nucleotide metabolism
- Digital Rights Management and Security
Sun Yat-sen University
2010-2024
Ministry of Education of the People's Republic of China
2023-2024
Tufts University
2017
Nankai University
2013
DeepFake face swapping presents a significant threat to online security and social media, which can replace the source in an arbitrary photo/video with target of entirely different person. In order prevent this fraud, some researchers have begun study adversarial methods against or manipulation. However, existing works mainly focus on white-box setting black-box driven by abundant queries, severely limits practical application these methods. To tackle problem, we introduce attack that does...
Recent studies have demonstrated that splenic extramedullary hematopoiesis (EMH) is an important mechanism for the accumulation of myeloid-derived suppressor cells (MDSCs) in tumor tissues, and thus contributes to disease progression. Icaritin, a prenylflavonoid derivative from plants Epimedium genus, has been implicated as novel immune-modulator could prolong survival hepatocellular carcinoma (HCC) patients. However, it unclear whether icaritin achieves its anti-tumor effects via regulation...
Few-Shot Image Classification (FSIC) aims to recognize novel image classes with limited data, which is significant in practice. In this paper, we consider the FSIC problem case of adversarial examples. This an extremely challenging issue because current deep learning methods are still vulnerable when handling examples, even massive labeled training samples. For problem, existing works focus on a network meta-learning fashion that depends numerous sampled few-shot tasks. comparison, propose...
Purpose Cancer-associated fibroblasts (CAFs) activated by cancer cells has a central role in development and malignant biological behavior colorectal (CRC). Adult do not express Snail, but Snail-positive are discovered the stroma of CRC reported to be key chemoresistance. However, reciprocal effect CAFs expressed Snail chemoresistance on underlying molecular mechanisms fully characterized. Materials Methods Snail-overexpressed 3T3 stable cell lines were generated lipidosome CT26 mixed with...
Metal-based chemoimmunotherapy has recently garnered significant attention for its capacity to stimulate tumor-specific immunity beyond direct cytotoxic effects. Such effects are usually caused by ICD via the activation of DAMP signals. However, metal complexes that can elicit antitumor immune responses other than have not yet been described. Herein, we report a rhodium complex (
Modern deep neural networks have made numerous breakthroughs in real-world applications, yet they remain vulnerable to some imperceptible adversarial perturbations. These tailored perturbations can severely disrupt the inference of current learning-based methods and may induce potential security hazards artificial intelligence applications. So far, training achieved excellent robustness against various attacks by involving examples during stage. However, existing primarily rely on optimizing...
Few-shot image classification (FSIC) is beneficial for a variety of real-world scenarios, aiming to construct recognition system with limited training data. In this article, we extend the original FSIC task by incorporating defense against malicious adversarial examples. This can be an arduous challenge because numerous deep learning-based approaches remain susceptible examples, even when trained ample amounts Previous studies on problem have predominantly concentrated meta-learning...
Despite intense efforts, the cause of Alzheimer’s disease is still not fully understood. A chemical and biochemical perspective could shed light on this disorder. Secondary bonding between calcium carbonyl oxygen atoms glycine valine might give rise to aggregates in brain, which may later result cell senescence. The decrease solubility caused by amino acid substitutions specific risk factors compounds insolubility issue likely triggers early-onset disease. Occasionally enhancement hydrogen...
2RDNTPA can be applied in fluorescence imaging of living cancer cells (HepG2) with red emission 620 nm and negligible cytotoxicity a half maximal inhibitory concentration much more than 100 μM.
Group re-identification (G-ReID) aims to identify the same group of persons across disjoint cameras. The key challenge G-ReID is robust feature extraction against potential layout and membership varitions. However, previous works focus more on appearance modeling less importance layout. In this paper, we propose a bi-directional propagation framework, which propagates information between member appearance. addition, spatial generation analyses image generates new images with different...