| 1. |
- Kristanl, Matej, et al.
(author)
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The Seventh Visual Object Tracking VOT2019 Challenge Results
- 2019
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In: 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW). - : IEEE COMPUTER SOC. - 9781728150239 ; , s. 2206-2241
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard short-term, long-term tracking and tracking with multi-channel imagery. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The dataset, the evaluation kit and the results are publicly available at the challenge website(1).
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| 2. |
- Kristan, Matej, et al.
(author)
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The first visual object tracking segmentation VOTS2023 challenge results
- 2023
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In: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
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| 3. |
- Chen, Anqi, et al.
(author)
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Highly Sensitive Graphene Oxide-based Fabry-Perot Low-frequency Acoustic Sensor With Low-coherence Polarized Demodulation Using Three-step Phase-Shifting Arctan Algorithms
- 2024
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In: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 42:17, s. 6115-6123
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Journal article (peer-reviewed)abstract
- Developing low-frequency acoustic senor with high sensitivity is crucial for diverse applications, ranging from seismic monitoring, military operations, to pipeline surveillance. Here, we have proposed a high-sensitivity graphene oxide (GO)-based Fabry-Perot low-frequency sensor, in which a 170 nm thick, large-area and uniformly GO film was prepared by a vacuum filtration method. To enhance the accuracy and stability of the sensor, a low-coherence interference system based on birefringent crystal blocks was designed utilizing a three-step phase-shifting arctangent algorithm. Our sensor exhibited a sensitivity of -93.48 dB re 1 rad/μPa at 6-60 Hz with a fluctuation of 0.6 dB. The minimum detectable pressure of the sensor was measured at 0.37 μPa/Hz1/2 @20 Hz with a signal to noise ratio of 135.41 dB. Overall, this sensor offers simplicity in preparation, high sensitivity, low detectable sound pressure, making it a significant asset for low-frequency acoustic applications.
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| 4. |
- Li, Danqin, et al.
(author)
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n-Doping of photoactive layer in binary organic solar cells realizes over 18.3% efficiency
- 2022
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In: Nano Energy. - : ELSEVIER. - 2211-2855 .- 2211-3282. ; 96
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Journal article (peer-reviewed)abstract
- Electronic doping of conjugated semiconductor plays a critical role in the fabrication of high efficiency organic optoelectronic devices. Here, we report an organic solar cell (OSC) by doping n-type DMBI-BDZC into one host binary bulk heterojunction (BHJ) photoactive layer comprised of a polymer donor PM6 and a nonfullerene acceptor Y6. The resulting champion device yields a significantly improved power conversion efficiency from 17.17% to 18.33% with an impressive fill factor of 80.20%. It is found that the electrically doped photoactive layer exhibits enhanced and balanced charge carrier mobilities, more effective exciton dissociation, longer carrier lifetime, and suppressed charge recombination with smaller energy loss. The dopant molecule DMBIBDZC also act as a surface morphology modifier of the photoactive layer with enhanced charge transport. This work demonstrates that manipulation of charge transport via adding a low concentration dopant into photoactive layer is a promising approach for further improvement of BHJ OSC performance.
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| 5. |
- Li, Deyang, et al.
(author)
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Ultraefficient Singlet Oxygen Generation from Manganese-Doped Cesium Lead Chloride Perovskite Quantum Dots
- 2020
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In: ACS Nano. - : American Chemical Society (ACS). - 1936-0851 .- 1936-086X. ; 14:10, s. 12596-12604
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Journal article (peer-reviewed)abstract
- Lead halide perovskites hold promise for photo-voltaics, lasers, and light-emitting diode (LED) applications, being known as light-harvesting or -emitting materials. Here we show that colloidal lead halide CsPbCl3 perovskite quantum dots (PQDs), when incorporating divalent manganese (Mn2+) ions, are able to produce spin-paired singlet oxygen molecules with over-unit quantum yield (similar to 1.08) in air conditions. Our mechanistic studies and atomic-level density functional theory calculations endorse an energy-migration-mediated quantum cutting process favoring multiple singlet oxygen generation (MSOG), in which one exciton-activated bulk Mn2+ ion (similar to 2.0 eV) inside the nanocrystal migrates its energy among the Mn2+ sublattice to two surface Mn2+ defect states (similar to 1.0 eV), followed by nonradiative energy transfers to two surrounding oxygen molecules. Moreover, superhydrophobicization of MSOG PQDs through silica-mediated polystyrene encapsulation prevents them from disintegrating in aqueous medium, enabling photodegradation of methyl orange at a rate even higher than that of the canonical titanium oxide photocatalyst. The observation of ultraefficient singlet oxygen generation in PQDs has implications for fields ranging from photodynamic therapy to photocatalytic applications.
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| 6. |
- Antonova, Rika, et al.
(author)
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Bayesian Optimization in Variational Latent Spaces with Dynamic Compression
- 2019
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In: Proceedings of the Conference on Robot Learning, CoRL 2019. - : ML Research Press. ; , s. 456-465
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Conference paper (peer-reviewed)abstract
- Data-efficiency is crucial for autonomous robots to adapt to new tasks and environments. In this work, we focus on robotics problems with a budget of only 10-20 trials. This is a very challenging setting even for data-efficient approaches like Bayesian optimization (BO), especially when optimizing higher-dimensional controllers. Previous work extracted expert-designed low-dimensional features from simulation trajectories to construct informed kernels and run ultra sample-efficient BO on hardware. We remove the need for expert-designed features by proposing a model and architecture for a sequential variational autoencoder that embeds the space of simulated trajectories into a lower-dimensional space of latent paths in an unsupervised way. We further compress the search space for BO by reducing exploration in parts of the state space that are undesirable, without requiring explicit constraints on controller parameters. We validate our approach with hardware experiments on a Daisy hexapod robot and an ABB Yumi manipulator. We also present simulation experiments with further comparisons to several baselines on Daisy and two manipulators. Our experiments indicate the proposed trajectory-based kernel with dynamic compression can offer ultra data-efficient optimization.
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| 7. |
- Antonova, Rika, et al.
(author)
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Bayesian optimization in variational latent spaces with dynamic compression
- 2020
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In: Proceedings of Machine Learning Research. ; , s. 456-465
-
Conference paper (peer-reviewed)abstract
- Data-efficiency is crucial for autonomous robots to adapt to new tasks and environments. In this work, we focus on robotics problems with a budget of only 10-20 trials. This is a very challenging setting even for data- efficient approaches like Bayesian optimization (BO), especially when optimizing higher-dimensional controllers. Previous work extracted expert-designed low-dimensional features from simulation trajectories to construct informed kernels and run ultra sample-efficient BO on hardware. We remove the need for expert-designed features by proposing a model and architecture for a sequential variational autoencoder that embeds the space of simulated trajectories into a lower-dimensional space of latent paths in an unsupervised way. We further compress the search space for BO by reducing exploration in parts of the state space that are undesirable, without requiring explicit constraints on controller parameters. We validate our approach with hardware experiments on a Daisy hexapod robot and an ABB Yumi manipulator. We also present simulation experiments with further comparisons to several baselines on Daisy and two manipulators. Our experiments indicate the proposed trajectory-based kernel with dynamic compression can offer ultra data-efficient optimization.
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| 8. |
- Hu, Tianyu, et al.
(author)
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Steric hindrance induced low exciton binding energy enables low-driving-force organic solar cells
- 2024
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In: Aggregate. - 2692-4560 .- 2766-8541. ; In Press
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Journal article (peer-reviewed)abstract
- Exciton binding energy (Eb) has been regarded as a critical parameter in charge separation during photovoltaic conversion. Minimizing the Eb of the photovoltaic materials can facilitate the exciton dissociation in low-driving force organic solar cells (OSCs) and thus improve the power conversion efficiency (PCE); nevertheless, diminishing the Eb with deliberate design principles remains a significant challenge. Herein, bulky side chain as steric hindrance structure was inserted into Y-series acceptors to minimize the Eb by modulating the intra- and intermolecular interaction. Theoretical and experimental results indicate that steric hindrance-induced optimal intra- and intermolecular interaction can enhance molecular polarizability, promote electronic orbital overlap between molecules, and facilitate delocalized charge transfer pathways, thereby resulting in a low Eb. The conspicuously reduced Eb obtained in Y-ChC5 with pinpoint steric hindrance modulation can minimize the detrimental effects on exciton dissociation in low-driving-force OSCs, achieving a remarkable PCE of 19.1% with over 95% internal quantum efficiency. Our study provides a new molecular design rationale to reduce the Eb.
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| 9. |
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| 10. |
- Li, Han, et al.
(author)
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A co-doped oxygen reduction catalyst with FeCu promotes the stability of microbial fuel cells
- 2022
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In: Journal of Colloid and Interface Science. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0021-9797 .- 1095-7103. ; 628, s. 652-662
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Journal article (peer-reviewed)abstract
- Air cathode microbial fuel cell (AC-MFC) cannot be used on a large scale because of its low oxygen reduction reaction (ORR) efficiency. Despite the fact that bimetallic catalysts can greatly enhance the oxygen reduction rate by regulating the electronic structure of the active site, the flaws of insufficient exposure of the active site and easy metal agglomeration limit its catalytic activity. Herein, we report on the preparation of a stable heteroatomic substrate using a copper material organic framework as a precursor, covered by Fe-based active sites. As a result of dipole-dipole interactions, the reduced product Fe2+ forms a weak Fe-O surface that is conducive to the adsorption of active substances. The presence of Fe-0 enhances the electrical conductivity of the catalytic, thus promoting ORR efficiency. Through redox coupling, the D -band center of Fe at FeCu@CN is optimized and brought close to the Fermi level to facilitate electron transfer. Notably, FeCu@CN demonstrates a superior power density of 2796.23 +/- 278.58 mW m(-3), far exceeding that of Pt/C (1363.93 +/- 102.56 mW m(-3)), in the application of microbial fuel cells (MFCs). Meanwhile, the MFC-loaded FeCu@CN maintains excellent stability and outstanding output voltage after 1000 h, which provides feasibility for large-scale application. (C) 2022 Elsevier Inc. All rights reserved.
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