A5071596217- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Video Surveillance and Tracking Methods
- Advanced Vision and Imaging
- Video Analysis and Summarization
- Image Retrieval and Classification Techniques
- Robot Manipulation and Learning
- Anomaly Detection Techniques and Applications
- Advanced Neural Network Applications
- Robotics and Sensor-Based Localization
- Advanced Image Processing Techniques
- Image and Video Stabilization
- Cancer Immunotherapy and Biomarkers
- Hand Gesture Recognition Systems
- Advanced SAR Imaging Techniques
- Infrared Target Detection Methodologies
- Melanoma and MAPK Pathways
- Natural Language Processing Techniques
- Disaster Response and Management
- Advanced Optical Imaging Technologies
- Spacecraft and Cryogenic Technologies
- Human Mobility and Location-Based Analysis
- Augmented Reality Applications
- Colorectal Cancer Treatments and Studies
- Multimodal Machine Learning Applications
Mayo Clinic in Arizona
2024-2025
Centre for Research and Technology Hellas
2012-2024
Information Technologies Institute
2010-2024
China Philanthropy Research Institute
2019-2022
Hellenic Open University
2022
Universidad Politécnica de Madrid
2016-2021
Information Technology Institute
2010-2021
Mayo Clinic in Florida
2021
WinnMed
2021
Aristotle University of Thessaloniki
2009
For patients with advanced non-small-cell lung cancer (NSCLC), dual immune checkpoint blockade (ICB) CTLA4 inhibitors and PD-1 or PD-L1 (hereafter, PD-(L)1 inhibitors) is associated higher rates of anti-tumour activity immune-related toxicities, when compared treatment alone. However, there are currently no validated biomarkers to identify which will benefit from ICB1,2. Here we show that NSCLC who have mutations in the STK11 and/or KEAP1 tumour suppressor genes derived clinical ICB...
Adopting effective techniques to automatically detect and identify small drones is a very compelling need for number of different stakeholders in both the public private sectors. This work presents three original approaches that competed grand challenge on “Drone vs. Bird” detection problem. The goal one or more appearing at some time point video sequences where birds other distractor objects may be also present, together with motion background foreground. Algorithms should raise an alarm...
9508 Background: Outcomes for pts with mMEL remain sobering despite access to available immunotherapies as the majority of are resistant or become refractory checkpoint blockade no approved treatments. CXCR1 and CXCR2 (CXCR1/2) signaling mediate myeloid immunosuppression MEL growth, inversely correlating anti-PD-1 response pt survival. SX-682 is an oral allosteric inhibitor CXCR1/2. As a single agent, increases tumor CD8+ T cell infiltration inhibits growth in mouse MEL. Methods: This phase...
We demonstrated a 3D holoscopic video system for 3DTV application. showed that using field lens and square aperture significantly reduces the vignetting problem associated with relay achieves over 95 percent fill factor. The main such is nonlinear distortion during image capturing, which can seriously affect reconstruction process display. mainly includes radial (intrinsic) microlens array perspective (extrinsic). This task of future work. Our results also show SS coding approach performs...
The popularity of Unmanned Aerial Vehicles (UAVs) is increasing year by and reportedly their applications hold great shares in global technology market. Yet, since UAVs can be also used for illegal actions, this raises various security issues that needs to encountered. Towards end, UAV detection systems have emerged detect further anticipate inimical drones. A very significant factor the maximum range which system's senses "see" an upcoming UAV. For those employ optical cameras detecting...
Super-Resolution (SR) is a fundamental computer vision task that aims to obtain high-resolution clean image from the given low-resolution counterpart. This paper reviews NTIRE 2021 Challenge on Video Super-Resolution. We present evaluation results two competition tracks as well proposed solutions. Track 1 develop conventional video SR methods focusing restoration quality. 2 assumes more challenging environment with lower frame rates, casting spatio-temporal problem. In each competition, 247...
This paper presents an experimental comparison of different approaches to learning from multi-labeled video data. We compare state-of-the-art multi-label methods on the Media mill Challenge dataset. employ MPEG-7 and SIFT-based global image descriptors independently in conjunction using variations stacking approach for their fusion. evaluate results comparing classifiers both A variety evaluation measures is used explore advantages disadvantages examined classifiers. Results give rise...
Crowd behavior analysis is an arduous task due to scale, light and crowd density variations. This paper aims develop a new method that can precisely detect classify abnormal in dense crowds. A two-stream network proposed uses heat-maps optical flow information events. Work on this has highlighted the lack of large scale relevant datasets fact dealing annotating such kind data highly time consuming demanding task. Therefore, synthetic dataset been created using Grand Theft Auto V engine which...
Traditional drone handheld remote controllers, although well-established and widely used, are not a particularly intuitive control method. At the same time, pilots normally watch video feed on smartphone or another small screen attached to remote. This forces them constantly shift their visual focus from vice-versa. can be an eye-and-mind-tiring stressful experience, as eyes change mind struggles merge two different points of view. paper presents solution based Microsoft’s HoloLens 2 headset...
Real-world CCTV footage often poses increased challenges in object tracking due to Pan-Tilt-Zoom operations, low camera quality and diverse working environments. Most relevant are moving background, motion blur severe scale changes. Convolutional neural networks, which offer state-of-the-art performance detection, increasingly utilized pursue a more efficient scheme. In this work, the use of heterogeneous training data augmentation is explored improve their detection rate challenging scenes....
In this paper, a novel approximate indexing scheme for efficient content-based image search and retrieval is presented, called Multi-Sort Indexing (MSIDX). The proposed analyzes high dimensional descriptor vectors, by employing the value cardinalities of their dimensions. dimensions' cardinalities, an inherent characteristic are number discrete values in As expected, significantly vary, due to existence several extraction methods. Moreover, different quantization normalization techniques...
Residual networks (ResNets) have introduced a milestone for the deep learning community due to their outstanding performance in diverse applications. They enable efficient training of increasingly networks, reducing difficulty and error. The main intuition behind them is that, instead mapping input information, they are residual part it. Since original work, lot extensions been proposed improve information mapping. In this paper, novel extension block inspired by linear dynamical systems...
This paper presents the video retrieval engine VERGE, which combines indexing, analysis and techniques in various modalities (i.e. textual, visual concept search). The functionalities of search are demonstrated through supported user interaction modes.
This work examines the possibility of exploiting, for purpose video segmentation to scenes, semantic information coming from analysis visual modality. information, in contrast low-level features typically used previous approaches, is obtained by application trained concept detectors such as those developed and evaluated part TRECVID High-Level Feature Extraction Task. A large number non-binary defining a high dimensional space. In this space, each shot represented vector detector confidence...
This paper presents an online, real-time, multiobject tracking algorithm based on a novel method for data association. Tracking multiple objects in real-world scenes includes several challenges, such as (a) object detectors with low detection accuracy, (b) false alarms, and (c) unmatched tracked objects. In this paper, we propose filtering the theory of censored by utilizing Adaptive Tobit Kalman filter to estimate object's position high accuracy. Furthermore, order deal alarms objects, use...